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Auteur B. Kleinschmit |
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Significance analysis of different types of ancillary geodata utilized in a multisource classification process for forest identification in Germany / Michael Förster in IEEE Transactions on geoscience and remote sensing, vol 52 n° 6 Tome 2 (June 2014)
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Titre : Significance analysis of different types of ancillary geodata utilized in a multisource classification process for forest identification in Germany Type de document : Article/Communication Auteurs : Michael Förster, Auteur ; B. Kleinschmit, Auteur Année de publication : 2014 Article en page(s) : pp 3453 - 3463 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image numérique
[Termes IGN] classification floue
[Termes IGN] données multisources
[Termes IGN] forêt
[Termes IGN] image à très haute résolution
[Termes IGN] télédétection spatialeRésumé : (Auteur) Ancillary geodata can supply information to enhance classification accuracy for a variety of remote-sensing applications. To understand the integration of different data into a knowledge-based multisource classification process, this paper evaluates the significance of geodata for the classification accuracy of a very high spatial resolution satellite image for the identification of forest types in Germany. The approach utilizes a fuzzy-logic classifier for the integration of a knowledge base, which combines spectral information with ancillary data layers. The results of the classification were used to test a method for evaluating the influence of the integration of single geodata, the effects on different classes, and the impacts of the applied rules. A microarray significance analysis (MSA) was used to evaluate the significance of the classification results, whereas an ISODATA clustering was utilized for visualizing. A sequence of 50 accuracy assessments of classifications with possible combinations of geodata and rules for the identified classes was derived. The resulting microarray of accuracy percentages of single classes and the overall classification was used for further investigation. The MSA supplies the measure of significance, called relative difference d(i). The MSA identified 11 classifications of positive significance (d(i) greater than 1.44) and three classifications of negative significance (d(i) lower than -2.87). In particular, classifications that contain all rules were rated as positive significant. Numéro de notice : A2014-310 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2273080 En ligne : https://doi.org/10.1109/TGRS.2013.2273080 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=33213
in IEEE Transactions on geoscience and remote sensing > vol 52 n° 6 Tome 2 (June 2014) . - pp 3453 - 3463[article]Réservation
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