ERS286: Advanced Topics in Remote Sensing

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).

Information:

Monday 9:00 - 12:00 am

Susan Ustin, Instructor (slustin@ucdavis.edu)

Course listserv: hyd286-s03@ucdavis.edu

Citations

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

Dark Object Subtraction / Haze Removal

Ahern, F. J., D. G. Goodenough, S. C. Jain, V. R. Rao, and G. Rochon. 1977. Use of clear lakes as standard reflectors for atmospheric measurements. Pages 731-755. Proceedings of the 11th International Symposium on Remote Sensing of Environment, Ann Arbor, MI.
Bierwirth, P. N. 1990. Mineral mapping and vegetation removal via data-calibrated pixel unmixing using multispectral images. International Journal of Remote Sensing 11:1999-2018.
Chavez, P. S. 1988. An Improved Dark-Object Subtraction Technique for Atmospheric Scattering Correction of Multispectral Data. Remote Sensing of Environment 24:459-479.
Moran, M. S., R. D. Jackson, P. N. Slater, and P. M. Teillet. 1992. Evaluation of Simplified Procedures for Retrieval of Land Surface Reflectance Factors from Satellite Sensor Output. Remote Sensing of Environment 41:169-184.
Ouaidrari, H., and E. F. Vermote. 2001. Operational atmospheric correction of Landsat TM data. Remote Sensing of Environment 70:4-15.
Pax-Lenney, M., C. E. Woodcock, S. A. Macomber, S. Gopal, and C. Song. 2001. Forest mapping with a generalized classifier and Landsat TM data. Remote Sensing of Environment 77:241-250.
Richards, J. A., and X. Jia. 1999. Error correction and registration of image data. Pages 39-74. Remote sensing digital image analysis : an introduction. Springer, Berlin ; New York.

Flat Field Calibration

Ben-Dor, E., and N. Levin. 2000. Determination of surface reflectance from raw hyperspectral data without simultaneous ground data measurements: a case study of the GER 63-channel sensor data acquired over Naan, Israel. International Journal of Remote Sensing 21:2053-2074.
Richards, J. A., and X. Jia. 1999. Interpretation of hyperspectral image data. Pages 313-337. Remote sensing digital image analysis : an introduction. Springer, Berlin ; New York.
Roberts, D. A., Y. Yamaguchi, and R. J. P. Lyon. 1986. Comparison of various techniques for calibration of AIS data. Pages 21-30. 2nd AIS Workshop. Jet Propulsion Laboratory, Pasadena, CA.

Empirical Line Calibration

Ben-Dor, E., F. A. Kruse, A. B. Lefkoff, and A. Banin. 1994. Comparison of 3 Calibration Techniques for Utilization of Ger 63-Channel Aircraft Scanner Data of Makhtesh-Ramon, Negev, Israel. Photogrammetric Engineering & Remote Sensing 60:1339-1354.
Farrand, W. H., R. B. Singer, and E. Merenyi. 1994. Retrieval of Apparent Surface Reflectance from Aviris Data - a Comparison of Empirical Line, Radiative Transfer, and Spectral Mixture Methods. Remote Sensing of Environment 47:311-321.
Ferrier, G. 1995. Evaluation of Apparent Surface Reflectance Estimation Methodologies. International Journal of Remote Sensing 16:2291-2297.
Kruse, F. A., K. S. Kierein-Young, and J. W. Boardman. 1990. Mineral mapping at Cuprite, Nevada with a 63-channel imaging spectrometer. Photogrammetric Engineering & Remote Sensing 56:83-92.
Moran, M. S., R. Bryant, K. Thome, W. Ni, Y. Nouvellon, M. P. Gonzalez-Dugo, and J. Qi. 2001. A refined empirical line approach for reflectance factor retrieval from Landsat-5 TM and Landsat-7 ETM+. Remote Sensing of Environment 78:71-82.
Perry, E. M., T. Warner, and P. Foote. 2000. Comparison of atmospheric modelling versus empirical line fitting for mosaicking HYDICE imagery. International Journal of Remote Sensing 21:799-803.
Richards, J. A., and X. Jia. 1999. Interpretation of hyperspectral image data. Pages 313-337. Remote sensing digital image analysis : an introduction. Springer, Berlin ; New York.
Roberts, D. A., Y. Yamaguchi, and R. J. P. Lyon. 1985. Calibration of Airborne Imaging Spectrometer data to percent reflectance using field spectral measurements. 19th International Symposium on Remote Sensing of Environment, Ann Arbor, MI.
Smith, G. M., and E. J. Milton. 1999. The use of the empirical line method to calibrate remotely sensed data to reflectance. International Journal of Remote Sensing 20:2653-2662.

Atmospheric COrrection Now (ACORN)

Analytical Imaging and Geophysics LLC 2002. ACORN 4.0 User's Guide. ImSpec LLC.
Goetz, A. 2002. Relative performance of HATCH and three other techniques for atmospheric correction of Hyperion and AVIRIS data. EO-1 Science Validation Meeting. NASA, Hilo, HI.
Miller, C. J. 2002. Performance assessment of ACORN atmospheric correction algorithm. Algorithms and Technologies for Multispectral, Hyperspectral, and Ultraspectral Imagery VIII; Aerosense 2002. SPIE, Orlando, FL.
Website: http://www.aigllc.com/acorn/intro.asp

FLAASH

Goetz, A. 2002. Relative performance of HATCH and three other techniques for atmospheric correction of Hyperion and AVIRIS data. EO-1 Science Validation Meeting. NASA, Hilo, HI.
Website: http://www.rsinc.com/envi/flaash.asp

ATCOR

Website: http://www.geosystems.de/atcor/index-info.html

HATCH

Goetz, A. 2002. Relative performance of HATCH and three other techniques for atmospheric correction of Hyperion and AVIRIS data. EO-1 Science Validation Meeting. NASA, Hilo, HI.

Last updated Sunday, April 20, 2003