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Auteur Luca Demarchi |
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Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 87 (January 2014)
[article]
Titre : Assessing the performance of two unsupervised dimensionality reduction techniques on hyperspectral APEX data for high resolution urban land-cover mapping Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Frank Canters, Auteur ; Claude Cariou, Auteur ; Giorgio Licciardi, Auteur ; Jonathan Cheung-Wai Chan, Auteur Année de publication : 2014 Article en page(s) : pp 166 - 179 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Airborne Prism Experiment
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] image APEX
[Termes IGN] image hyperspectrale
[Termes IGN] Perceptron multicoucheRésumé : (Auteur) Despite the high richness of information content provided by airborne hyperspectral data, detailed urban land-cover mapping is still a challenging task. An important topic in hyperspectral remote sensing is the issue of high dimensionality, which is commonly addressed by dimensionality reduction techniques. While many studies focus on methodological developments in data reduction, less attention is paid to the assessment of the proposed methods in detailed urban hyperspectral land-cover mapping, using state-of-the-art image classification approaches. In this study we evaluate the potential of two unsupervised data reduction techniques, the Autoassociative Neural Network (AANN) and the BandClust method – the first a transformation based approach, the second a feature-selection based approach – for mapping of urban land cover at a high level of thematic detail, using an APEX 288-band hyperspectral dataset. Both methods were tested in combination with four state-of-the-art machine learning classifiers: Random Forest (RF), AdaBoost (ADB), the multiple layer perceptron (MLP), and support vector machines (SVM). When used in combination with a strong learner (MLP, SVM) BandClust produces classification accuracies similar to or higher than obtained with the full dataset, demonstrating the method’s capability of preserving critical spectral information, required for the classifier to successfully distinguish between the 22 urban land-cover classes defined in this study. In the AANN data reduction process, on the other hand, important spectral information seems to be compromised or lost, resulting in lower accuracies for three of the four classifiers tested. Detailed analysis of accuracies at class level confirms the superiority of the SVM/Bandclust combination for accurate urban land-cover mapping using a reduced hyperspectral dataset. This study also demonstrates the potential of the new APEX sensor data for detailed mapping of land cover in spatially and spectrally complex urban areas. Numéro de notice : A2014-018 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.10.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.10.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32923
in ISPRS Journal of photogrammetry and remote sensing > vol 87 (January 2014) . - pp 166 - 179[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2014011 RAB Revue Centre de documentation En réserve L003 Disponible Multiple endmember unmixing of CHRIS/Proba imagery for mapping impervious surfaces in urban and suburban environments / Luca Demarchi in IEEE Transactions on geoscience and remote sensing, vol 50 n° 9 (October 2012)
[article]
Titre : Multiple endmember unmixing of CHRIS/Proba imagery for mapping impervious surfaces in urban and suburban environments Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Frank Canters, Auteur ; Jonathan Cheung-Wai Chan, Auteur ; T. Van De Voorde, Auteur Année de publication : 2012 Article en page(s) : pp 3409 - 3424 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] Flandre (Belgique)
[Termes IGN] image PROBA-CHRIS
[Termes IGN] occupation du sol
[Termes IGN] précision infrapixellaire
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) In this paper, the potential of Compact High-Resolution Imaging Spectrometer (CHRIS)/Project for On-Board Autonomy data for impervious surface mapping is tested in a mixed urban/suburban/rural environment including part of the city of Leuven (Belgium) using multiple endmember unmixing. Various unmixing scenarios are compared, using different threshold values for the RMSE criterion applied to select the proper model for unmixing each pixel. Validation based on 25-cm aerial photography shows that the use of threshold values that favor the application of models with a small number of endmembers performs better compared to scenarios that make use of models with more endmembers. Detailed analysis of model selection for pixels with different land-cover composition indicates that the error in fraction estimation is partly related to spectral confusion between impervious surface types and bare soil, leading to the selection of inappropriate models for the unmixing. In spite of the spectral similarity of soil and impervious surface endmembers, average fractional error for impervious surfaces, vegetation, and bare soil is around 15%, which demonstrates the potential of CHRIS data for mapping the major physical components of the urban/suburban environment at the subpixel scale. Numéro de notice : A2012-449 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2011.2181853 Date de publication en ligne : 15/03/2012 En ligne : https://doi.org/10.1109/TGRS.2011.2181853 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31895
in IEEE Transactions on geoscience and remote sensing > vol 50 n° 9 (October 2012) . - pp 3409 - 3424[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 065-2012091 RAB Revue Centre de documentation En réserve L003 Exclu du prêt Mapping impervious surfaces from superresolution enhanced CHRIS/Proba imagery using multiple endmember unmixing / Luca Demarchi in ISPRS Journal of photogrammetry and remote sensing, vol 72 (August 2012)
[article]
Titre : Mapping impervious surfaces from superresolution enhanced CHRIS/Proba imagery using multiple endmember unmixing Type de document : Article/Communication Auteurs : Luca Demarchi, Auteur ; Jonathan Cheung-Wai Chan, Auteur ; J. Ma, Auteur ; Frank Canters, Auteur Année de publication : 2012 Article en page(s) : pp 99 - 112 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] image à ultra haute résolution
[Termes IGN] image PROBA-CHRIS
[Termes IGN] occupation du sol
[Termes IGN] satellite agile
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) In this paper, the potential of superresolution (SR) image reconstruction methods for sub-pixel land-cover mapping in dense urban areas is studied. A multiple endmember approach (MESMA) is used for unmixing both original hyperspectral CHRIS/Proba and SR enhanced CHRIS/Proba data. Validation based on high resolution orthophotos (25 cm) shows that land-cover fraction maps generated from SR-enhanced CHRIS/Proba data (9 m) have a lower overall fractional error compared to the land-cover fractions produced from the original CHRIS data (18 m), when validating both results at the 18 m resolution. Validation of SR results at the 9 m resolution produces an overall mean absolute error (OMAE) of 16.7% compared to an OMAE of 14.3% at the 18 m resolution, with the original data, yet the impervious surface map produced at 9 m has a much higher level of detail than the original map, better representing the built-up pattern of the urban environment. Detailed analysis of impervious surface mapping results for different reference proportion intervals points at smaller average fractional errors for impervious surface fractions produced from SR-enhanced data when validation is done at the original 18 m resolution, over the entire range of proportions. Only for pixels not containing any impervious surface cover the fractional error is marginally higher than with the original data. These results demonstrate the potential of SR-enhanced data for more accurate impervious surface mapping in dense and heterogeneous urban areas. Numéro de notice : A2012-496 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2012.05.015 En ligne : https://doi.org/10.1016/j.isprsjprs.2012.05.015 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=31942
in ISPRS Journal of photogrammetry and remote sensing > vol 72 (August 2012) . - pp 99 - 112[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2012061 SL Revue Centre de documentation Revues en salle Disponible