Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie
Multi-temporal images acquired at high spatial and temporal resolution are an important tool for detecting change and analyzing trends, especially in agricultural applications. However, to insure a reliable use of this kind of data, a rigorous radiometric normalization step is required. Normalization can be addressed by performing an atmospheric correction of each image in the time series. The main problem is the difficulty of obtaining an atmospheric characterization at a given acquisition date. In this paper, we investigate whether relative radiometric normalization can substitute for atmospheric correction. We develop an automatic method for relative radiometric normalization based on calculating linear regressions between unnormalized and reference images. Regressions are obtained using the reflectances of automatically selected invariant targets. We compare this method with an atmospheric correction method that uses the 6S model. The performances of both methods are compared using 18 images from of a SPOT 5 time series acquired over Reunion Island. Results obtained for a set of manually selected invariant targets show excellent agreement between the two methods in all spectral bands: values of the coefficient of determination (r²) exceed 0.960, and bias magnitude values are less than 2.65. There is also a strong correlation between normalized NDVI values of sugarcane fields (r² = 0.959). Despite a relative error of 12.66% between values, very comparable NDVI patterns are observed.
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dig-cirad-fr-5453262024-01-28T16:06:53Z http://agritrop.cirad.fr/545326/ http://agritrop.cirad.fr/545326/ Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie. El Hajj Mahmoud, Bégué Agnès, Lafrance Bruno, Hagolle O., Dedieu G., Rumeau M.. 2008. Sensors (8) : 2774-2791.https://doi.org/10.3390/s8042774 <https://doi.org/10.3390/s8042774> Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie El Hajj, Mahmoud Bégué, Agnès Lafrance, Bruno Hagolle, O. Dedieu, G. Rumeau, M. eng 2008 Sensors U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques télédétection Saccharum conditions météorologiques radio mesure (activité) méthodologie expérimentation normalisation image spot imagerie par satellite métrologie http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_6725 http://aims.fao.org/aos/agrovoc/c_29565 http://aims.fao.org/aos/agrovoc/c_6424 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_2758 http://aims.fao.org/aos/agrovoc/c_7366 http://aims.fao.org/aos/agrovoc/c_16343 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_6a3cd403 La Réunion France http://aims.fao.org/aos/agrovoc/c_6543 http://aims.fao.org/aos/agrovoc/c_3081 Multi-temporal images acquired at high spatial and temporal resolution are an important tool for detecting change and analyzing trends, especially in agricultural applications. However, to insure a reliable use of this kind of data, a rigorous radiometric normalization step is required. Normalization can be addressed by performing an atmospheric correction of each image in the time series. The main problem is the difficulty of obtaining an atmospheric characterization at a given acquisition date. In this paper, we investigate whether relative radiometric normalization can substitute for atmospheric correction. We develop an automatic method for relative radiometric normalization based on calculating linear regressions between unnormalized and reference images. Regressions are obtained using the reflectances of automatically selected invariant targets. We compare this method with an atmospheric correction method that uses the 6S model. The performances of both methods are compared using 18 images from of a SPOT 5 time series acquired over Reunion Island. Results obtained for a set of manually selected invariant targets show excellent agreement between the two methods in all spectral bands: values of the coefficient of determination (r²) exceed 0.960, and bias magnitude values are less than 2.65. There is also a strong correlation between normalized NDVI values of sugarcane fields (r² = 0.959). Despite a relative error of 12.66% between values, very comparable NDVI patterns are observed. article info:eu-repo/semantics/article Journal Article info:eu-repo/semantics/publishedVersion http://agritrop.cirad.fr/545326/1/document_545326.pdf application/pdf Cirad license info:eu-repo/semantics/openAccess https://agritrop.cirad.fr/mention_legale.html https://doi.org/10.3390/s8042774 10.3390/s8042774 info:eu-repo/semantics/altIdentifier/doi/10.3390/s8042774 info:eu-repo/semantics/altIdentifier/purl/https://doi.org/10.3390/s8042774 info:eu-repo/semantics/reference/purl/http://www.mdpi.org/sensors/papers/s8042774.pdf |
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U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques télédétection Saccharum conditions météorologiques radio mesure (activité) méthodologie expérimentation normalisation image spot imagerie par satellite métrologie http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_6725 http://aims.fao.org/aos/agrovoc/c_29565 http://aims.fao.org/aos/agrovoc/c_6424 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_2758 http://aims.fao.org/aos/agrovoc/c_7366 http://aims.fao.org/aos/agrovoc/c_16343 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_6a3cd403 http://aims.fao.org/aos/agrovoc/c_6543 http://aims.fao.org/aos/agrovoc/c_3081 U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques télédétection Saccharum conditions météorologiques radio mesure (activité) méthodologie expérimentation normalisation image spot imagerie par satellite métrologie http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_6725 http://aims.fao.org/aos/agrovoc/c_29565 http://aims.fao.org/aos/agrovoc/c_6424 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_2758 http://aims.fao.org/aos/agrovoc/c_7366 http://aims.fao.org/aos/agrovoc/c_16343 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_6a3cd403 http://aims.fao.org/aos/agrovoc/c_6543 http://aims.fao.org/aos/agrovoc/c_3081 |
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U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques télédétection Saccharum conditions météorologiques radio mesure (activité) méthodologie expérimentation normalisation image spot imagerie par satellite métrologie http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_6725 http://aims.fao.org/aos/agrovoc/c_29565 http://aims.fao.org/aos/agrovoc/c_6424 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_2758 http://aims.fao.org/aos/agrovoc/c_7366 http://aims.fao.org/aos/agrovoc/c_16343 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_6a3cd403 http://aims.fao.org/aos/agrovoc/c_6543 http://aims.fao.org/aos/agrovoc/c_3081 U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques télédétection Saccharum conditions météorologiques radio mesure (activité) méthodologie expérimentation normalisation image spot imagerie par satellite métrologie http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_6725 http://aims.fao.org/aos/agrovoc/c_29565 http://aims.fao.org/aos/agrovoc/c_6424 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_2758 http://aims.fao.org/aos/agrovoc/c_7366 http://aims.fao.org/aos/agrovoc/c_16343 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_6a3cd403 http://aims.fao.org/aos/agrovoc/c_6543 http://aims.fao.org/aos/agrovoc/c_3081 El Hajj, Mahmoud Bégué, Agnès Lafrance, Bruno Hagolle, O. Dedieu, G. Rumeau, M. Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie |
description |
Multi-temporal images acquired at high spatial and temporal resolution are an important tool for detecting change and analyzing trends, especially in agricultural applications. However, to insure a reliable use of this kind of data, a rigorous radiometric normalization step is required. Normalization can be addressed by performing an atmospheric correction of each image in the time series. The main problem is the difficulty of obtaining an atmospheric characterization at a given acquisition date. In this paper, we investigate whether relative radiometric normalization can substitute for atmospheric correction. We develop an automatic method for relative radiometric normalization based on calculating linear regressions between unnormalized and reference images. Regressions are obtained using the reflectances of automatically selected invariant targets. We compare this method with an atmospheric correction method that uses the 6S model. The performances of both methods are compared using 18 images from of a SPOT 5 time series acquired over Reunion Island. Results obtained for a set of manually selected invariant targets show excellent agreement between the two methods in all spectral bands: values of the coefficient of determination (r²) exceed 0.960, and bias magnitude values are less than 2.65. There is also a strong correlation between normalized NDVI values of sugarcane fields (r² = 0.959). Despite a relative error of 12.66% between values, very comparable NDVI patterns are observed. |
format |
article |
topic_facet |
U30 - Méthodes de recherche U10 - Informatique, mathématiques et statistiques télédétection Saccharum conditions météorologiques radio mesure (activité) méthodologie expérimentation normalisation image spot imagerie par satellite métrologie http://aims.fao.org/aos/agrovoc/c_6498 http://aims.fao.org/aos/agrovoc/c_6725 http://aims.fao.org/aos/agrovoc/c_29565 http://aims.fao.org/aos/agrovoc/c_6424 http://aims.fao.org/aos/agrovoc/c_4668 http://aims.fao.org/aos/agrovoc/c_12522 http://aims.fao.org/aos/agrovoc/c_2758 http://aims.fao.org/aos/agrovoc/c_7366 http://aims.fao.org/aos/agrovoc/c_16343 http://aims.fao.org/aos/agrovoc/c_36761 http://aims.fao.org/aos/agrovoc/c_6a3cd403 http://aims.fao.org/aos/agrovoc/c_6543 http://aims.fao.org/aos/agrovoc/c_3081 |
author |
El Hajj, Mahmoud Bégué, Agnès Lafrance, Bruno Hagolle, O. Dedieu, G. Rumeau, M. |
author_facet |
El Hajj, Mahmoud Bégué, Agnès Lafrance, Bruno Hagolle, O. Dedieu, G. Rumeau, M. |
author_sort |
El Hajj, Mahmoud |
title |
Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie |
title_short |
Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie |
title_full |
Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie |
title_fullStr |
Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie |
title_full_unstemmed |
Relative radiometric normalization and atmospheric correction of a SPOT 5 time serie |
title_sort |
relative radiometric normalization and atmospheric correction of a spot 5 time serie |
url |
http://agritrop.cirad.fr/545326/ http://agritrop.cirad.fr/545326/1/document_545326.pdf |
work_keys_str_mv |
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_version_ |
1792496930638528512 |