The long term calibration history of the Landsat 5 TM instrument has recently been defined using a time series of desert sites in Northern Africa. This correction is based on the assumption that the atmosphere is invariant and the reflectance of each site is approximately constant and Lambertian over time. As a result, the top of the atmosphere reflection is assumed constant when corrected for variations in the solar elevation angle and earth-sun distance. While this is true to first order and is the basis for all current temporal calibration, there are multiple known sources of residual error in the data. A methodology is presented for reducing the variation in pseudo-invariant site trending data based on correction for the BRDF. This work establishes a means to use DIRSIG to model the L5 calibration site. It combines a digital elevation map and desert atmosphere with a surface BRDF to reduce the residual errors in the calibration data. A set of Landsat 7 ETM+ calibration days is utilized to optimize the surface reflectance properties used in DIRSIG. These optimized parameters are then used to model the L5 TM calibration days. The results of the DIRSIG modeling are compared to the solar elevation angle and time of year trends of the original data and analyzed for their effectiveness at describing and reducing the residual errors. A major goal of this effort is to understand the contribution that BRDFs make to the current calibration errors and to develop methods that are robust enough to be applicable to a wider range of sites to enable extension of the methodology to earlier data sets (e.g. Landsat MSS). Additionally, while Landsat has a 30 m reflective resolution, the pseudo-invariant site calibration approach is valid for all spatial resolutions. Depending on another instrument's field of view, the BRDF error reduction technique used by L5 TM could either be used on the same desert calibration site or on a subsection of the area.

Library of Congress Subject Headings

Landsat satellites--Calibration; Artificial satellites in remote sensing--Calibration; Remote sensing--Data processing

Publication Date


Document Type


Student Type


Department, Program, or Center

Chester F. Carlson Center for Imaging Science (COS)


Schott, John


Note: imported from RIT’s Digital Media Library running on DSpace to RIT Scholar Works. Physical copy available through RIT's The Wallace Library at: G70.6 .A64 2010


RIT – Main Campus