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Remote Sensing of Environment 113 (2009) 893–903

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Remote Sensing of Environment
j o u r n a l h o m e p a g e : w w w. e l s ev i e r. c o m / l o c a t e / r s e

Summary of current radiometric calibration coefficients for Landsat MSS, TM, ETM+, and EO-1 ALI sensors
Gyanesh Chander a,⁎, Brian L. Markham b, Dennis L. Helder c
a b c

SGT, Inc.contractor to the U.S. Geological Survey (USGS) Earth Resources Observation and Science (EROS) Center, Sioux Falls, SD 57198-0001, USA National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), Greenbelt, MD 20771, USA South Dakota State University (SDSU), Brookings, SD 57007, USA

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This paper provides a summary of thecurrent equations and rescaling factors for converting calibrated Digital Numbers (DNs) to absolute units of at-sensor spectral radiance, Top-Of-Atmosphere (TOA) reflectance, and at-sensor brightness temperature. It tabulates the necessary constants for the Multispectral Scanner (MSS), Thematic Mapper (TM), Enhanced Thematic Mapper Plus (ETM+), and Advanced Land Imager (ALI) sensors. Theseconversions provide a basis for standardized comparison of data in a single scene or between images acquired on different dates or by different sensors. This paper forms a needed guide for Landsat data users who now have access to the entire Landsat archive at no cost. © 2009 Elsevier Inc. All rights reserved.

Article history: Received 10 December 2008 Received in revised form 16 January 2009 Accepted17 January 2009 Keywords: Landsat MSS, TM, ETM+ EO-1 ALI Radiometric characterization & calibration At-sensor spectral radiance Top-of-atmosphere reflectance At-sensor brightness temperature

1. Introduction The Landsat series of satellites provides the longest continuous record of satellite-based observations. As such, Landsat is an invaluable resource for monitoring global change and is aprimary source of medium spatial resolution Earth observations used in decision-making (Fuller et al., 1994; Townshend et al.,1995; Goward & Williams,1997; Vogelmann et al., 2001; Woodcock et al., 2001; Cohen & Goward, 2004; Goward et al., 2006; Masek et al., 2008; Wulder et al., 2008). To meet observation requirements at a scale revealing both natural and human-induced landscape changes, Landsatprovides the only inventory of the global land surface over time on a seasonal basis (Special issues on Landsat, 1984, 1985, 1997, 2001, 2003, 2004, 2006). The Landsat Program began in early 1972 with the launch of the first satellite in the series. As technological capabilities increased, so did the amount and quality of image data captured by the various sensors onboard the satellites. Table 1presents general information about each Landsat satellite. Landsat satellites can be classified into three groups, based on sensor and platform characteristics. The first group consists of Landsat 1 (L1), Landsat 2 (L2), and Landsat 3 (L3), with the Multispectral Scanner (MSS) sensor and the Return Beam Vidicon (RBV) camera as payloads on a “NIMBUS-like” platform. The spatial resolution of the

⁎Corresponding author. Tel.: +1 605 594 2554. E-mail address: gchander@usgs.gov (G. Chander). 1 Work performed under USGS contract 08HQCN0005. 0034-4257/$ – see front matter © 2009 Elsevier Inc. All rights reserved. doi:10.1016/j.rse.2009.01.007

MSS sensor was approximately 79 m (but often processed to pixel size of 60 m), with four bands ranging from the visible blue to the NearInfrared (NIR)wavelengths. The MSS sensor on L3 included a fifth band in the thermal infrared wavelength, with a spectral range from 10.4 to 12.6 μm. The L1–L3 MSS sensors used a band-naming convention of MSS-4, MSS-5, MSS-6, and MSS-7 for the blue, green, red, and NIR bands, respectively (Markham & Barker, 1983). This designation is obsolete, and to be consistent with the TM and ETM+ sensors, the MSS bands are...
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