ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer)

Written by Jeffrey Gillan

Other Names:

None known

Agency/Company Operating the Sensor

Jointly managed by NASA and Japan’s Ministry of International Trade and Industry


ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) is one of five imaging instruments flying on the Terra satellite launched in 1999 as part of NASA’s Earth Observing System. It is used to gather detailed data on surface temperature, emissivity, reflectance, and elevation at a relatively high spatial resolution. ASTER gathers data in 14 spectral bands: 3 visible and 11 in the infrared region of the electromagnetic spectrum. It has a nadir and backward facing Band 3 which gives it the unique ability to create digital elevation models based on stereo images. It has a revisit time of 16 days which can be a limitation for studying rapidly changing surface conditions. There might also be costs associated with acquiring some images.

Similar Sensors

Landsat Thematic Mapper 5 (TM5), Landsat Thematic Mapper 7 (TM7)

Sensor Specifications

The ASTER sensor consists of three separate subsystems. ASTER has a sun-synchronous polar orbit meaning it crosses over any given latitude at the same time each day. The satellite revisits the same area every 16 days.

Spectral Bands/Wavelengths

Visible and Near Infrared Subsystem: 8 bits, 60km swath width
Band Resolution Wavelength µm Description
1 (nadir) 15m 0.52-0.60 Green
2 (nadir) 15m 0.63-0.69 Red
3 (nadir) 15m 0.76-0.86 Near Infrared
3 (backward) 15m 0.76-0.86 Near Infrared
Short Wave Infrared Subsystem: 8 bits, 60km swath width
Band Resolution Wavelength µm Description
4 30m 1.600-1.700 Short Wave Infrared
5 30m 2.145-2.185 Short Wave Infrared
6 30m 2.185-2.225 Short Wave Infrared
7 30m 2.235-2.285 Short Wave Infrared
8 30m 2.295-2.365 Short Wave Infrared
9 30m 2.360-2.430 Short Wave Infrared
Thermal Infrared Subsystem: 12 bits, 60km swath width
Band Resolution Wavelength µm Description
10 90m 8.125-8.475 Thermal Infrared
11 90m 8.475-8.825 Thermal Infrared
12 90m 8.925-9.275 Thermal Infrared
13 90m 10.25-10.95 Thermal Infrared
14 90m 10.95-11.65 Thermal Infrared

Cost, Acquisition, Licensing

Unlike the Landsat program that acquires and archives all images, ASTER provides images on-demand and will only gather data on an area if a request has been submitted. Pre-existing ASTER images are archived and available through the Reverb/Echo system or the Land Processes Distributed Active Archive Center (LPDAAC) Data Pool A suite of products at different processing levels are available through these two sources. All existing level 1B products through the Data Pool are available at no cost. Higher processes products may have costs involved.

If your area of interest has not been archived or acquired yet, please click here for instructions on how to request an image acquisition.

ASTER Standard Products

Level Product Description
1A Radiance at sensor Image data plus radiometric and geometric coefficients. Data are separated by telescope.
1AE Radiance at sensor Expedited L1AE data product created from ASTER Expedited Level-0.
1BE Registered radiance at sensor Expedited L1BE data product created from ASTER. Expedited Level – 1AE
2A Registered radiance at sensor 1A data with radiometric and geometric coefficients applied
2 Decorrelation stretch Enhanced color composites for each telescope
2 Brightness temperature Radiance at the sensor converted to temperature
2 Surface radiance Radiance corrected for atmospheric effects
2 Surface reflectance VNIR, SWIR Derived from surface radiance with topographic corrections
2 Surface kinetic temperature Temperature-emissivity separation algorithm applied to atmospherically corrected surface radiance data.
2 Surface emissivity Temperature-emissivity separation algorithm applied to atmospherically corrected surface radiance data.
3 Polar Surface and Cloud Classification Classifies each pixel of polar scenes into one of eight classes: water cloud, ice cloud, aerosol/dust, water, land, snow/ice, slush ice, and shadow.
3 Digital elevation model DEM produced by stereo correlation of nadir and aft band 4 data
3 Orthorectified 15 orthorectified L1B radiance images in GeoTiff
3 Orthorectified DEM 15 orthorectified L1B images + DEM

Image format

ASTER images typically come in a HDF-EOS file format but can be converted to Geotiff files in several projections.Tools for carrying out data transformations can be found at:

Examples of Rangeland Uses

  • Heine et al (2007) used ASTER imagery to create land cover maps to assess the condition of high altitude pastures
  • Phillips and Beeri (2008) used ASTER and Landsat images to estimate net ecosystem exchange in the Northern Great Plains
  • Garcia et al (2008) used surface temperature and reflectance from ASTER images to study land degradation risk in a semi-arid region of Spain
  • Hewson et al (2008) used thermal ASTER imagery to extract soil textural information

Software/Hardware Requirements

Java is required for viewing and selecting data in the LPDAAC Data Pool.

ASTER images can be converted into GeoTiff format making is compatible with ESRI ArcGIS and other GIS platforms. The images can be manipulated and processed in remote sensing software packages such as ENVI and ERDAS Imagine.

Additional Information


  • Garcia, Monica, Cecilio Oyonarte, Luis Villagarcia, Sergio Contreras, Francisco Domingo, Juan Puigdefabregas (2008), Monitoring land degradation risk using ASTER data: The non-evaporative fraction as an indicator of ecosystem function, Remote Sensing of the Environment, Vol. 12, pp. 3720-3736.
  • Heine, Erwin, Monika Kriechbaum, and Franz Suppan (2007), Assessment of the condition of the high altitude pastures in south Tibet supported by land cover maps derived from Aster Satellite Data, 9th International Symposium on High Mountain Remote Sensing Cartography, pp. 193-200.
  • Hewson, R. D., G. R. Taylor, and L. W. Whitborn (2008), Application of TIR imagery and spectroscopy for the extraction of soil textural information at Fowlers Gap, Western New South Wales, Australia, unpublished report, IEEE International Geoscience & Remote Sensing Symposium.
  • Jenson, John R. (2007), Remote Sensing of the Environment: An Earth resource perspective, second edition, Prentice Hall series in geographic information science, Upper Saddle River, NJ.
  • Phillips, Rebecca L. and Ofer Beeri (2008), Scaling-up knowledge of growing-season net ecosystem exchange for long-term assessment of North Dakota grasslands under the Conservation Reserve Program, Global Change Biology, Vol. 14, pp. 1008-1017.

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