Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies

Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (abs...

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Autores principales: Paolini, L., Grings, F., Sobrino, J., Jiménez Muñoz, J.C., Karszenbaum, H.
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Acceso en línea:http://hdl.handle.net/20.500.12110/paper_01431161_v27_n4_p685_Paolini
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spelling todo:paper_01431161_v27_n4_p685_Paolini2023-10-03T14:59:15Z Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies Paolini, L. Grings, F. Sobrino, J. Jiménez Muñoz, J.C. Karszenbaum, H. Algorithms Calibration Principal component analysis Radiometry Sensor data fusion Absolute correction Multi-date studies Multi-sensor studies Radiometric correction Relative correction Remote sensing Landsat radiometric method remote sensing Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM+ images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a cross-calibration between TM and ETM+ images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo-invariant features (PIFs) selected through band-to-band PCA analysis. We present a new algorithm for PIFs selection in order to improve normalization results. A post-correction evaluation index (Quadratic Difference Index (QD)), and post-classification and change detection results were used to evaluate the performance of the methods. Only the absolute correction method and the new relative correction method presented in this paper show good post-correction and post-classification results (QD index ≈ 0; overall accuracy >80%; kappa >0.65) for all the images used. Land cover change estimations based on uncorrected images present unrealistic change rates (two to three times those obtained with corrected images), which highlights the fact that radiometric corrections are necessary in multi-date multi-sensor land cover change analysis. © 2006 Taylor & Francis. JOUR info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/2.5/ar http://hdl.handle.net/20.500.12110/paper_01431161_v27_n4_p685_Paolini
institution Universidad de Buenos Aires
institution_str I-28
repository_str R-134
collection Biblioteca Digital - Facultad de Ciencias Exactas y Naturales (UBA)
topic Algorithms
Calibration
Principal component analysis
Radiometry
Sensor data fusion
Absolute correction
Multi-date studies
Multi-sensor studies
Radiometric correction
Relative correction
Remote sensing
Landsat
radiometric method
remote sensing
spellingShingle Algorithms
Calibration
Principal component analysis
Radiometry
Sensor data fusion
Absolute correction
Multi-date studies
Multi-sensor studies
Radiometric correction
Relative correction
Remote sensing
Landsat
radiometric method
remote sensing
Paolini, L.
Grings, F.
Sobrino, J.
Jiménez Muñoz, J.C.
Karszenbaum, H.
Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies
topic_facet Algorithms
Calibration
Principal component analysis
Radiometry
Sensor data fusion
Absolute correction
Multi-date studies
Multi-sensor studies
Radiometric correction
Relative correction
Remote sensing
Landsat
radiometric method
remote sensing
description Radiometric corrections serve to remove the effects that alter the spectral characteristics of land features, except for actual changes in ground target, becoming mandatory in multi-sensor, multi-date studies. In this paper, we evaluate the effects of two types of radiometric correction methods (absolute and relative) for the determination of land cover changes, using Landsat TM and Landsat ETM+ images. In addition, we present an improvement made to the relative correction method addressed. Absolute correction includes a cross-calibration between TM and ETM+ images, and the application of an atmospheric correction protocol. Relative correction normalizes the images using pseudo-invariant features (PIFs) selected through band-to-band PCA analysis. We present a new algorithm for PIFs selection in order to improve normalization results. A post-correction evaluation index (Quadratic Difference Index (QD)), and post-classification and change detection results were used to evaluate the performance of the methods. Only the absolute correction method and the new relative correction method presented in this paper show good post-correction and post-classification results (QD index ≈ 0; overall accuracy >80%; kappa >0.65) for all the images used. Land cover change estimations based on uncorrected images present unrealistic change rates (two to three times those obtained with corrected images), which highlights the fact that radiometric corrections are necessary in multi-date multi-sensor land cover change analysis. © 2006 Taylor & Francis.
format JOUR
author Paolini, L.
Grings, F.
Sobrino, J.
Jiménez Muñoz, J.C.
Karszenbaum, H.
author_facet Paolini, L.
Grings, F.
Sobrino, J.
Jiménez Muñoz, J.C.
Karszenbaum, H.
author_sort Paolini, L.
title Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies
title_short Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies
title_full Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies
title_fullStr Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies
title_full_unstemmed Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies
title_sort radiometric correction effects in landsat multi-date/multi-sensor change detection studies
url http://hdl.handle.net/20.500.12110/paper_01431161_v27_n4_p685_Paolini
work_keys_str_mv AT paolinil radiometriccorrectioneffectsinlandsatmultidatemultisensorchangedetectionstudies
AT gringsf radiometriccorrectioneffectsinlandsatmultidatemultisensorchangedetectionstudies
AT sobrinoj radiometriccorrectioneffectsinlandsatmultidatemultisensorchangedetectionstudies
AT jimenezmunozjc radiometriccorrectioneffectsinlandsatmultidatemultisensorchangedetectionstudies
AT karszenbaumh radiometriccorrectioneffectsinlandsatmultidatemultisensorchangedetectionstudies
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