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Radarsat-1


Contributors: Megan Kanaga Creutzburg

Other Names:

None known

Agency/Company Operating the Sensor

Description

RADARSAT-1 is a satellite that was launched in 1995 by the Canadian Space Agency, in collaboration with NASA and other agencies. It carries a Synthetic Aperture Radar (SAR) sensor, which is a powerful microwave instrument that can transmit and receive signals to obtain detailed images of the Earth.

SAR sensors are a form of active remote sensing where, instead of recording the amount of sunlight reflected from a surface or radiation emitted from a surface (e.g., thermal imaging), radar pulses are emitted from the sensor and then the reflected responses are recorded. Radar sensors operate in the microwave region of the electromagnetic spectrum. RADARSAT-1 and RADARSAT-2 operate in the C-band frequency range of the electromagnetic spectrum at a wavelength of 5.6 cm.

Radar is a ranging sensor - meaning that it detects the distance to objects by timing how long it takes for emitted pulses to return to the sensor (LIDAR operates on the same principle using pulses of a different wavelength). This information is converted to elevation by processing the radar signal. By examining other properties of the radar responses (e.g., the amount of the signal that is returned), other properties of the surface (and in some cases even sub-surface properties like sub-canopy or sub-soil information) can be determined. For example, areas with high vegetative cover scatter much of the radar signal and will show up darker in a radar image than those with lots of bare ground that reflect more of the radar signal.

Also, because radar sensors emit their own radiation, they can function day or night and can often image through clouds or smoke, making them very versatile.

Similar Sensors

Sensor Specifications

Spectral Bands/Wavelengths

RADARSAT-1 uses a SAR sensor to image the Earth in a single microwave band, the C-band, at a wavelength of 5.6 cm.

Image footprint or swath width

RADARSAT-1 offers modes with varying image resolution and image footprint:

  • Fine – covers an area of 50 km by 50 km (2500 km²)
  • Standard – covers an area of 100 km by 100 km (10,000 km²)
  • ScanSAR – covers a 500 km by 500 km (250,000 km²) area


RADARSAT-1 also has the ability to direct its beam at different angles.

Image resolution

RADARSAT-1 offers modes with varying image resolution and image footprint:

  • Fine – spatial resolution of 10 meters
  • Standard – spatial resolution of 30 meters
  • ScanSAR wide – spatial resolution of 100 meters

Return Interval

RADARSAT-1 circles the Earth 14 times a day and has an orbital period of 100.7 minutes. The same orbit path is repeated every 24 days, so the satellite can take the same image, with the same beam mode and beam position, every 24 days.

Availability

1995 to present.

Cost, Acquisition, Licensing

See the MDA Geospatial Services website for information about RADARSAT-1 products and costs http://gs.mdacorporation.com/products/sensor/radarsat/rs1_price_ca.asp

Image format

Images are available in CEOS format.

Examples of Rangeland Uses

  • Blanco et al. (2009) used RADARSAT and ASTER sensors to map vegetation communities and landforms in Argentina
  • Drunpob et al. (2004 and 2005) measured soil moisture using RADARSAT images
  • Zhang et al. (2006) used RADARSAT data to assess grassland heterogeneity using texture analysis

Software/Hardware Requirements

Processing of RADARSAT data will require remote sensing software and may require statistical/mathematical modeling software, depending on the application.

Sample Image


RADARSAT-1 image of a landscape showing: a) active dunes, b) natural vegetation, c) grassland/scrubland, and d) rock fragments. Dunes reflect very little of the emitted radar beams and appear dark in the image, whereas rocks reflect most of the emitted radiation and thus appear light in color (source: Blanco et al. 2009).



Soil moisture map (left) derived from a RADARSAT SAR map (right) (source: Drunpob et al. 2004).

Additional Information

References

  • Blanco, P.D., G.I. Metternicht, and H.F. Del Valle. 2009. Improving the discrimination of vegetation
  • and landform patterns in sandy rangelands: a synergistic approach. International Journal of Remote Sensing 30: 2579-2605.
  • Drunpob, A., N.B. Chang, M. Beaman, and C. Wyatt. 2004. Soil moisture analysis using RADARSAT satellite image in the Choke Canyon Reservoir Watershed, South Texas. Geoscience and Remote Sensing Symposium, IGARSS ’04 Proceedings, 20-24 September 2004.
  • Drunpob, A., N.B. Chang, M. Beaman, C. Wyatt C. Slater. 2005. Seasonal Soil Moisture Variation Analysis using RADARSAT-1 Satellite Image in a Semi-arid Coastal Watershed. Analysis of Multi-Temporal Remote Sensing Images, 2005 International Workshop, 16-18 May 2005.
  • Kwarteng, A.Y. 2009. Vegetation analysis in desert environment using SAR imagery. 2009. Anais XIV Simpósio Brasileiro de Sensoriamento Remoto, Natal, Brasil, 25-30 abril 2009, INPE, p. 7291-7298.
  • Makkeasorn, A., N-B. Chang, and J. Li. 2009. Seasonal change detection of riparian zones with remote sensing images and genetic programming in a semi-arid watershed. Journal of Environmental Management 90: 1069-1080.
  • Taft, O.W., S.M. Haig, and C. Kiilsgaard. 2003. Use of Radar Remote Sensing (RADARSAT) to Map Winter Wetland Habitat for Shorebirds in an Agricultural Landscape. Environmental Management Vol. 32: 268-281.
  • van der Sanden, J.J. 2004. Anticipated applications potential of RADARSAT-2 data. Canadian Journal of Remote Sensing 30: 369-379.
  • Zhang, C., X. Guo, J. Wilmshurst, and R. Sissons. 2006. Application of RADARSAT imagery to grassland biophysical heterogeneity assessment. Canadian Journal of Remote Sensing 32: 281-287.

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remote_sensor_types/radarsat-1.txt · Last modified: 2012/03/08 16:20 by jgillan