Global Forest Watch Using High Resolution Synthetic Aperture Radar

Forests always have been an important for all human beings and animals. For some forests provide shelter and some forests are source of livelihood.


Monitoring global forest footprint is of particular interest and importance for scientific community. Remote sensing technique has played a vital role in in determination and estimation of global forest cover.


Since 1972, US Landsat satellite program (optical imaging) is well known for measuring forest cover. There are certain regions in the world such as tropical forest, which are under cloud cover most of the time in a year. Optical remote sensing senor couldn’t see beyond the clouds collect and hence put the limitation on global forest cover.





Global mosaics show phased-array type L-band synthetic aperture radar-2 color composites in (top) horizontal transmission/ reception (HH), horizontal transmission/vertical reception (HV), and HH/HV modes in red, green and blue, respectively, and (bottom) the corresponding map of forest areas (green)/non-forest areas (yellow)

Credit: SPIE


With advancement in technology, a new technology known as synthetic aperture radar (SAR) has revolutionized the remote sensing technology. SAR can see through the clouds and even in nights.


In a study by Masanobu Shimada et. al., titled “High-resolution satellite radar for mapping changes in global forest cover” has produced the global forest cover map for 2007–2010.


A high-resolution synthetic aperture radar (SAR) uses low-frequency microwaves, which enable forest and non-forest/other land use to be easily differentiated under all weather conditions. As of now only three SAR frequency bands are available for use in space. Of these three bands, the L-band of 23 cm wavelength has a higher ability to distinguish forest areas than the C-band of 5.6cm and X-band of 3 cm wavelength.


Scientist have used the phased-array type L-band SAR (PALSAR) was a high resolution multi-polarization low-noise radar, which was installed on the Advanced Land Observing Satellite (ALOS). ALOS has collected 2.1 million SAR images of 70*70 km in dimension of entire globe. They have also applied PALSAR data in HV mode to estimate forest cover and its annual variation.








Color composite image showing four-year variation of forest cover in western Indonesia and Malaysia.Credit: SPIE



Scientists have generated four global mosaics of PALSAR horizontal transmission/horizontal reception (HH) and HV polarization data at 25 m spatial resolution using data acquired annually from 2007 to 2010.


The first estimated global forest area was 38,542,500 sq. km from the ALOS/PALSAR data set, following the Landsat-based estimation of forest area as 40,656,570 sq. km . The difference can probably be attributed to a difference in the sensitivity of optical and L-band SAR techniques in measuring forest cover.


In summary, L-band SAR backscatter provides the basis of information regarding forest and non-forest areas on a global scale. The enhanced maps and classification of land use provide a new global resource for documenting the changing extent of forests and also offer opportunities to quantify historical and future changes through comparison with data from the Japanese Earth Resources Satellite-1 SAR (1992–1998) and ALOS-2/PALSAR-2 (from 2014).

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Why SWIR Band in Remote Sensing?

Each object has its own spectral signature, which is also the basic principle of remote sensing. Today we have satellites with various sensors collecting data in Visible light, Near Infrared (NIR), Thermal Infrared (TIR), Panchromatic and Shortwave Infrared (SWIR ).

If we have these many sensors, why we need SWIR sensor?

SWIR  is immediate adjacent to NIR in electromagnetic spectrum  and refers to non-visible light falling roughly between 1400 and 3000 nanometers (nm) in wavelength.

SWIR Sensor vs Visible Light Sensor:

SWIR light is reflective in nature and bounce of objects much like visible light. But SWIR light is not visible to human eyes. As a result of reflective nature, SWIR light has shadow and contrast in its imagery (contrast depends upon the radiometric resolution of sensor). Unlike visible light imagery SWIR light image is not in color. This makes objects easily recognizable and yields one of the tactical advantages of the SWIR, namely, object or individual identification.

Visible blue, green, and red of Landsat 8 satellite. Credit: USGS

SWIR Sensor vs Thermal Sensor:

Thermal sensors are another important type of sensor as they can see heat and so use for  thermal mapping. Instead of measuring the temperature of the air (as weather station do), they capture the ground heat. Thermal sensor capture imagery of warm object against a cool background and they do not provide good resolution  (100 m in Landsat 8) imagery. Whereas SWIR sensors can have high resolution (30 m in Landsat 8, 3.7/7.5 meter in WorldView 3) and can actually identify what object is. They also pinpoint sites of active burning, detect hot spots and estimate of where the fire is burning the hottest, so that response efforts can be directed most efficiently.

Thermal infrared, or TIR bands of Landsat 8 satellite. Credit: USGS

Like SWIR light imagery they are also not in color. SWIR Sensors are smaller in size than Thermal sensor, hence a lighter payload for satellite.

SWIR Sensor vs Panchromatic Sensor:

Panchromatic sensor capture imagery in single band (black and white film) instead of collecting visible color (red, green, blue) separately, it combines them into one channel or band. Panchromatic sensor can see more light at once and can have very high spatial resolutions  (31 cm in WorldView 3) than any other sensor types. But panchromatic sensor can not see in night and through smoke.

Panchromatic band of Landsat 8 satellite . Credi: USGS

SWIR sensor may not have similar spatial resolution but they have a high spatial resolution (3.7/7.5 meter in WorldView 3, 30 m in Landsat 8). SWIR sensor can see in night and through smoke.

SWIR Sensor vs NIR Sensor:

Near Infrared sensor are extremely important for ecology because healthy plants reflect it – the water in their leaves scatters the wavelengths back into the sky. They can be used for vegetation monitoring, crop stress etc. By comparing it with other bands, we get indexes like NDVI, which let us measure plant health more precisely than if we only looked at visible greenness. But NIR sensor do not tell us about the geology, rocks etc.

Near infrared, or NIR of Landsat 8 satellite. Credit: USGS

False-color image by using SWIR as red, NIR as green, and deep blue as blue of Landsat 8 satellite. Credit: USGS

SWIR sensors are particularly useful for telling wet earth from dry earth, and for geology: rocks and soils that look similar in other bands often have strong contrasts in SWIR. SWIR sensors discriminates moisture content of soil and vegetation and penetrates thin clouds.

I. The SWIR image is a “false color” composite made from three of the eight SWIR bands (bands 6, 3, and 1) that coincidentally give an orange color to the fire. Credit: DigitalGlobe

II. The SWIR bands penetrate smoke to differing degrees. SWIR band 8 has the best smoke penetration. Credit: DigitalGlobe

III. Further zoom around the burn area in which no smoke is visible. Credit: Digitalglobe

IV. SWIR band 8 has the best smoke penetration; here is a zoomed in shot of the fire line in which no smoke is visible.    Credit: DigitalGlobe

Possible Applications of SWIR Sensors:

• Mineral exploration
• Wildfire response (can penetrate through smoke)
• Food security
• Mining/Geology
• Urban feature identification (such as roofing and construction materials)
• Vegetation
• Petroleum (e.g. an oil spill)
• Snow and Ice discrimination
• Soil moisture estimation

Advantages of SWIR

• High sensitivity
• High resolution
• Provide imagery in day and night
• Can see penetrates thin clouds
• Covert illumination
• SWIR sensors are small in size, hence lighter payload and can be mounted on UAV
• Can see through the smoke
• Atmospheric aerosols have lesser effect on SWIR bands.

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Europe’s Sentinel-2A Satellite Delivers its First Images of Earth

29 June 2015 – Just four days after being lofted into orbit, Europe’s Sentinel-2A satellite delivered its first images of Earth, offering a glimpse of the ‘colour vision’ that it will provide for the Copernicus environmental monitoring programme.

With a swath width of 290 km, the satellite’s first acquisition began in Sweden and made a strip-like observation through central Europe and the Mediterranean, ending in Algeria.

The data were relayed in real time to Italy’s Matera ground station, where teams eagerly awaited their arrival for processing.

Northwest Italy and southern France.
Credit: ESA

While northern and central Europe were mostly cloudy, Italy’s typical sunny weather allowed the teams to get their first glimpse of the multispectral instrument’s capabilities over the northwestern part of the country and the French Riviera – and they were excited by what they saw. With a ground resolution of 10 m per pixel, the images show individual buildings in Milan, agricultural plots along the Po River, and ports along the southern French coast.

“This new satellite will be a game changer in Earth observation for Europe and for the European Copernicus programme,” said Philippe Brunet, Director for Space Policy, Copernicus and Defence at the European Commission.

The Director of ESA’s Earth Observation Programmes, Volker Liebig, commented, “Sentinel-2 will enable us to provide data for the programme’s land monitoring services and will be the base for a wide spectrum of applications reaching from agriculture to forestry, environmental monitoring to urban planning.”

The multispectral imager is being calibrated during the commissioning phase – which will take about three months to complete – but the quality of these first images already exceeds expectations.

Po Valley, Italy.
Credit: ESA

In addition to demonstrating the imager’s high resolution, these initial data also foreshadow the mission’s land-monitoring applications in areas such as agriculture, inland and coastal waters and land-cover mapping.

The imager’s 13 spectral bands, from the visible and the near infrared to the shortwave infrared at different spatial resolutions, take land monitoring to an unprecedented level. In fact, Sentinel-2 is the first optical Earth observation mission of its kind to include three bands in the ‘red edge’, which provide key information on the state of vegetation.

This weekend’s activities also demonstrated that the operational processor works flawlessly, paving the way for the mission’s systematic data generation to come.

Sentinel-2A is the second satellite for Europe’s Copernicus programme, following the Sentinel-1A radar satellite launched last year.

Designed as a two-satellite mission, Sentinel-2 will provide optical imagery on a five-day revisit cycle once its twin, Sentinel-2B, is launched in 2016.

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