Written by Jeffrey Gillan
Other Names:
Landsat 4, Landsat 5, TM4, TM5
Agency/Company Operating the Sensor
Jointly managed by NASA and USGS
Description
The Landsat program, started in 1972, is one of the mainstays of NASA’s earth-observation program. Landsat Thematic Mapper is a sensor flying on Landsat 4 and 5 satellites. Landsat 4 was launched in 1982 and ended operation in 1993. Landsat 5 was launched in 1984 and continued to acquire imagery, in 7 spectral bands until November 2011. The satellite is currently not operational. The Landsat satellites were designed to be of use to a variety of fields like forestry, agriculture, geology, and land-use planning, and the choice of spectral bands for the Landsat satellites was geared toward discriminating different types and amounts of vegetation. Landsat’s strengths are generally seen to be its regular acquisition schedule (revisits each spot on the earth every 16 days), long-term data archive (image with comparable specifications is available from 1982), and relatively rich spectral information (not as rich as hyperspectral data, but more bands than most high-resolution satellites like IKONOS or Quickbird). Limitations of Landsat data are that it is only a moderate-resolution image source (30m multispectral data, 120m thermal infrared), and the fixed acquisition schedule makes it sometimes difficult to acquire imagery for a particular place at a particular time (especially important if clouds or smoke are frequent).
Prior to the launch of Landsat 8 in early 2013, Landsat 5 TM was important for data continuity due to the failure of Landsat 7’s scan line corrector in 1993. Landsat has the deepest archive of systematic satellite images of any sensor orbiting the earth, a fact that is invaluable for studying global change. Landsat 5 TM provided a link to the next generation. NASA’s Landsat 8 has similar specifications to its predecessors.
Similar Sensors
• Landsat 8
• Landsat ETM 7
• ASTER
• SPOT 1-4
Sensor Specifications
Landsat TM has 7 spectral bands; 3 in the visible range and 4 in the infrared range. Band 6 is specifically sensitive to thermal infrared radiation to measure surface temperature. The band wavelengths were chosen for their value in discriminating vegetation type, water penetration, plant and soil moisture measurements, and identification of hydrothermal alteration in certain rock types. All of the bands have a 30m pixel size except band 6 which has a spatial resolution of 120m.
Spectral Bands/Wavelengths
| Band | Resolution | Wavelength µm | Description |
|---|---|---|---|
| 1 | 30m | 0.45-0.52 | Blue |
| 2 | 30m | 0.53-0.61 | Green |
| 3 | 30m | 0.63-0.69 | Red |
| 4 | 30m | 0.78-0.90 | Near Infrared |
| 5 | 30m | 1.55-1.75 | Short-wave Infrared |
| 6 | 60m | 10.4-12.5 | Thermal Infrared |
| 7 | 30m | 2.09-2.35 | Short-wave Infrared |
Image footprint or swath width
Landsat TM data is delivered in scenes that measure 115 miles (185km ) by 106 miles (170km).
Return Interval
Landsat 4 and 5 are on the WRS-2 orbit path and revisits the same spot on the earth every 16 days. Because Landsat 4 and 5 are in a sun-synchronous orbit, they cross the equator between 9:30am and 10:00am each day.
Cost, Acquisition, Licensing
As of October 2008, all Landsat TM archived imagery and new acquisitions are free. You can search for, order, and download Landsat TM data from a number of sources including: the USGS Global Visualization Viewer (GLOVIS), the USGS http://earthexplorer.usgs.gov/, or Landsat.org. The archives data back to 1982 for some scenes.
Image format
Format and delivery options for Landsat TM imagery varies with where you order and download the imagery. Images are commonly shipped as TIFF image files – one image for each band. Alternatively, data may come in USGS’ HDF format. Most images come as raw digital numbers and need to be transformed into radiance or reflectance for many applications.
Examples of Rangeland Uses
- Tueller (1989) discusses remote sensing applications for rangeland management
- Paruelo et al (2000) used Landsat TM images to estimate primary production for pasture stocking rates
- Tanser and Palmer (1999) used Landsat TM images to assess degradation of semi-arid landscapes
Because of the similarity between TM 4, 5 and eTM 7, the references for Landsat 7 also apply here.
Software/Hardware Requirements
Landsat imagery is one of the most ubiquitous satellite image types, and a lot of effort has gone into making it easy to access and use. For the most part, Landsat imagery can be used in ArcGIS or other GIS applications without any special processing. Most Landsat images obtained either through USGS or another provider are distributed in TIFF image format with one band per file. For the purposes of making it easier to handle, manipulate, and display the imagery, most people combine all of the separate image bands into a single, multi-band image file using an image-processing package like ENVI or ERDAS Imagine.
Landsat images are not terribly big or difficult to process by today’s computing standards. In a TIFF image format, the file for a single 30m band is approximately 53MB. As long as you are dealing with a study area that is contained within one or a few Landsat scenes, you should not need any special computer hardware to be able to use Landsat imagery.
Additional Information
- USGS Landsat 5 Mission http://landsat.usgs.gov/about_landsat5.php
- NASA Landsat program http://landsat.gsfc.nasa.gov/
- Landsat 4 wikipedia page http://en.wikipedia.org/wiki/Landsat_4
- Landsat calibration and other technical documents that can be used to convert digital numbers to radiance and reflectance http://landsat.usgs.gov/tools_project_documents.php
- NASA’s Data Continuity Mission http://ldcm.nasa.gov/
- Landsat image gallery http://landsat.usgs.gov/gallery.php
References
- 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.
- Paruelo, J. M, M. Oesterheld, C. M. Di Bella, M. Arzadum, J. Lafontaine, M. Cahuepe, C. M. Rebella (2000), Estimation of primary production of subhumid rangelands from remote sensing data, Applied Vegetation Science, 3, pp. 189-195
- Tanser, Frank C. and Anthony R. Palmer (1999), The application of a remotely-sensed diversity index to monitor degradation patterns in a semi-arid heterogeneous, South African landscape, Journal of Arid Environments, vol. 43, issue 4, pp. 477-484
- Tueller, Paul T. (1989), Remote sensing technology for rangeland management applications, Journal of Rangeland Management, vol. 42, no. 6, pp. 442-453.