TY - JOUR
T1 - Radiometric rectification
T2 - Toward a common radiometric response among multidate, multisensor images
AU - Hall, F. G.
AU - Strebel, D. E.
AU - Nickeson, J. E.
AU - Goetz, S. J.
N1 - Funding Information:
This paper is a contribution of the FIFE staff science research effort. It draws on data supplied to the FIFE information system by many FIFE investigators. Comments and discussion by C. Bruegge and M. Spanner were particularly helpful, as were the referee's careful reviews and comments. The Konza Prairie Natural Research Area within the FIFE site is owned by the Nature Conservancy, funded in part by the National Science Foundation, and operated by the Division of Biology at Kansas State University. This work was partially performed under contract to the National Aeronautic and Space Administration by employees of Versar, Inc. and ST Systems Corp.
PY - 1991/1
Y1 - 1991/1
N2 - A common radiometric response is required for quantitative analysis of multiple satellite images of a scene acquired on different dates with different sensors. We describe a technique to "radiometrically rectify" multiple Landsat images of a scene to a reference image, and evaluate it using a pair of Landsat 5 images acquired 2 years apart. All rectified images should appear as if they were acquired with the same sensor, while observing through the atmospheric and illumination conditions of the reference image. If atmospheric optical depth and sensor calibration date are available for the reference image, then an atmospheric correction algorithm may be used to correct all the rectified images to absolute surface reflectance. The "radiometric rectification" algorithm identifies "radiometric control sets," i.e., sets of scene landscape elements with a mean reflectance which is expected to change little with time. The average digital count values of these radiometric control sets are used to calculate linear transforms relating digital count values between images. We evaluate the technique empirically with a pair of Landsat 5 TM images of a scene for which surface reflectance and atmospheric optical depth data are available. We also examine its performance under a wide range of atmospheric conditions using simulations based on atmospheric models. We find that the radiometric rectification algorithm performed well for the visible and near infrared bands, adjusting surface reflectance for the effects of relative atmospheric differences to within 1%. The performance is not as good for the midinfrared bands on TM. There are several possible causes for this; we could not determine which was the most important. We conclude from these studies that for scenes containing reflectance stable elements, radiometric rectification should be a useful alternative to atmospheric radiative transfer codes and sensor calibration approaches when reliable atmospheric optical depth data or calibration coefficients are not available. When atmospheric optical data and sensor calibration information are available for one of a sequence of radiometrically rectified images, an atmospheric radiative transfer code may be used to correct each image in the sequence to absolute surface reflectance.
AB - A common radiometric response is required for quantitative analysis of multiple satellite images of a scene acquired on different dates with different sensors. We describe a technique to "radiometrically rectify" multiple Landsat images of a scene to a reference image, and evaluate it using a pair of Landsat 5 images acquired 2 years apart. All rectified images should appear as if they were acquired with the same sensor, while observing through the atmospheric and illumination conditions of the reference image. If atmospheric optical depth and sensor calibration date are available for the reference image, then an atmospheric correction algorithm may be used to correct all the rectified images to absolute surface reflectance. The "radiometric rectification" algorithm identifies "radiometric control sets," i.e., sets of scene landscape elements with a mean reflectance which is expected to change little with time. The average digital count values of these radiometric control sets are used to calculate linear transforms relating digital count values between images. We evaluate the technique empirically with a pair of Landsat 5 TM images of a scene for which surface reflectance and atmospheric optical depth data are available. We also examine its performance under a wide range of atmospheric conditions using simulations based on atmospheric models. We find that the radiometric rectification algorithm performed well for the visible and near infrared bands, adjusting surface reflectance for the effects of relative atmospheric differences to within 1%. The performance is not as good for the midinfrared bands on TM. There are several possible causes for this; we could not determine which was the most important. We conclude from these studies that for scenes containing reflectance stable elements, radiometric rectification should be a useful alternative to atmospheric radiative transfer codes and sensor calibration approaches when reliable atmospheric optical depth data or calibration coefficients are not available. When atmospheric optical data and sensor calibration information are available for one of a sequence of radiometrically rectified images, an atmospheric radiative transfer code may be used to correct each image in the sequence to absolute surface reflectance.
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U2 - 10.1016/0034-4257(91)90062-B
DO - 10.1016/0034-4257(91)90062-B
M3 - Article
AN - SCOPUS:0026002269
SN - 0034-4257
VL - 35
SP - 11
EP - 27
JO - Remote Sensing of Environment
JF - Remote Sensing of Environment
IS - 1
ER -