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Comparison of tree-based classification algorithms in mapping burned forest areas / Dilek Kucuk Matci in Geodetski vestnik, vol 64 n° 3 (September - November 2020)  

Public [article]  inGeodetski vestnik > vol 64 n° 3 (September - November 2020) . - 13 p. Titre : Comparison of tree-based classification algorithms in mapping burned forest areas Type de document : Article/Communication Auteurs : Dilek Kucuk Matci, Auteur ; Resul Comert, Auteur ; Ugur Avdan, Auteur Année de publication : 2020 Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Slovène (slv) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse comparative [Termes IGN] analyse d'image orientée objet [Termes IGN] bassin méditerranéen [Termes IGN] carte forestière [Termes IGN] classification dirigée [Termes IGN] classification par arbre de décision [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] image Landsat-8 [Termes IGN] incendie de forêt [Termes IGN] matrice de confusion [Termes IGN] pansharpening (fusion d'images) [Termes IGN] Rotation Forest classification [Termes IGN] Turquie [Termes IGN] zone sinistrée Résumé : (auteur) In this study, we compared the performance of tree-based classification algorithms – Random Forest (RF), Rotation Forest (RotF), J48, The Alternating Decision Tree (ADTree), Forest by Penalising Attributes (Forest PA), Logical Analysis of Data Algorithm (LADTree) and Functional Trees (FT) – for mapping burned forest areas within the Mediterranean region in Turkey. Object-based image analysis (OBIA) was performed to pan-sharpened the Landsat 8 images. Four different burned areas, namely Kumluca, Adrasan, Anamur, and Alanya, were used as study areas. Kumluca, Anamur, and Alanya regions were used as training areas, and Adrasan region was used as the test area. Obtained results were evaluated with confusion matrix and statistically significant analysis. According to the results, FT and RotF produced more accurate results than other algorithms. Also, the results obtained with these algorithms are statistically significant. Numéro de notice : A2020-626 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.15292/geodetski-vestnik.2020.03.348-360 Date de publication en ligne : 23/08/2020 En ligne : https://doi.org/10.15292/geodetski-vestnik.2020.03.348-360 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96087 [article]

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