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...
Guardado en:
| Publicado: |
2006
|
|---|---|
| Materias: | |
| Acceso en línea: | https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01431161_v27_n4_p685_Paolini http://hdl.handle.net/20.500.12110/paper_01431161_v27_n4_p685_Paolini |
| Aporte de: |
| id |
paper:paper_01431161_v27_n4_p685_Paolini |
|---|---|
| record_format |
dspace |
| spelling |
paper:paper_01431161_v27_n4_p685_Paolini2023-06-08T15:11:46Z Radiometric correction effects in Landsat multi-date/multi-sensor change detection studies 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. 2006 https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01431161_v27_n4_p685_Paolini 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 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. |
| 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 |
| publishDate |
2006 |
| url |
https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01431161_v27_n4_p685_Paolini http://hdl.handle.net/20.500.12110/paper_01431161_v27_n4_p685_Paolini |
| _version_ |
1768542120387280896 |