HYD286 (Spring 2003): Advanced Topics in Remote Sensing

Calibration Methods

Course Goals

This quarter we will investigate various ways that have been developed to correct remote sensing data for atmospheric effects. As remote sensing data analyses move from more statistically based to more physically based methods, correct calibration of data to surface reflectance is an ever increasing requirement. However, methods are not well described in the literature and knowledge is largely based on personal experience. Because the science is still emerging there is a lot of uncertainty in performing these corrections and in interpreting data in the published literature.

Methods include various empirical methods and radiative transfer models that attempt to account for wavelength specific absorption and scattering. Empirical methods include ratio, subtraction, empirical line corrections. The RT models we will review and discuss include ACORN, ATCOR, FLAASH and HATCH. Each method will be discussed in class and students will present relevant literature for review. Students will analyze two datasets (one without topography and low atmospheric water vapor and one with topography and variable atmosphere) with each of these methods as part of a term project which will be written and presented to the class. The class materials will become part of a web-based white paper on methods and if appropriate, we will seek to publish it as a review in a remote sensing journal (e.g., Remote Sensing Reviews).


Monday 9:00 - 12:00 am

Susan Ustin, Instructor (slustin@ucdavis.edu)

Course listserv: hyd286-s03@ucdavis.edu


Endnote Library (last updated 4/20/2003): hyd286-s03.enl

Dark Object Subtraction / Haze Removal

Flat Field Calibration

Empirical Line Calibration

Atmospheric COrrection Now (ACORN)





 Last updated Sunday, April 20, 2003