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Use of the Bradley-Terry model to quantify association in remotely sensed images / Alfred Stein in IEEE Transactions on geoscience and remote sensing, vol 43 n° 4 (April 2005)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 43 n° 4 (April 2005) . - pp 852 - 856 Titre : Use of the Bradley-Terry model to quantify association in remotely sensed images Type de document : Article/Communication Auteurs : Alfred Stein, Auteur ; J. Aryal, Auteur ; G. Gort, Auteur Année de publication : 2005 Article en page(s) : pp 852 - 856 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse comparative [Termes IGN] classification barycentrique [Termes IGN] classification par la distance de Mahalanobis [Termes IGN] classification par maximum de vraisemblance [Termes IGN] estimation de précision [Termes IGN] estimation des paramètres [Termes IGN] image Ikonos [Termes IGN] image Terra-ASTER [Termes IGN] Pays-Bas Résumé : (Auteur) Thematic maps prepared from remotely sensed images require a statistical accuracy assessment. For this purpose, the k-statistic is often used. This statistic does not distinguish between whether one unit is classified as another, or vice versa. In this paper, the Bradley-Terry (BT) model is applied for accuracy assessment. This model compares categories pairwise. The probability of one class over another class is estimated as well as the expected values of class pixels. The study is illustrated with an Advanced Spaceborne Thermal Emission and Reflection Radiometer image from the Netherlands, to which a maximum-likelihood classification with the Euclidean distance is applied. An error matrix is generated using an IKONOS image from the same area as ground truth. It is shown to which degree the BT model extends the K-statistic. A comparison with the Mahalanobis distance is made. Standardization is carried out to overcome problems emerging from the fact that a common BT model does not include the number of correctly classified pixels. The study shows how the BT model serves as an alternative to the usual k-statistic. Numéro de notice : A2005-193 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2005.843569 En ligne : https://doi.org/10.1109/TGRS.2005.843569 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=27330 [article]

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