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Discriminating pure Tamarix species and their putative hybrids using field spectrometer / Solomon G. Tesfamichael in Geocarto international, vol 37 n° 25 ([01/12/2022])  

Public [article]  inGeocarto international > vol 37 n° 25 [01/12/2022] . - pp 7733 - 7752 Titre : Discriminating pure Tamarix species and their putative hybrids using field spectrometer Type de document : Article/Communication Auteurs : Solomon G. Tesfamichael, Auteur ; Solomon W. Newete, Auteur ; Elhadi Adam, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 7733 - 7752 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Afrique du sud (état) [Termes IGN] apprentissage automatique [Termes IGN] canopée [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] espèce exotique envahissante [Termes IGN] essence indigène [Termes IGN] Extreme Gradient Machine [Termes IGN] feuille (végétation) [Termes IGN] image Landsat-8 [Termes IGN] image Sentinel-MSI [Termes IGN] image SPOT 6 [Termes IGN] image Worldview [Termes IGN] spectroradiomètre [Termes IGN] Tamarix (genre) Résumé : (auteur) South Africa is home to a native Tamarix species, while two were introduced in the early 1900s to mitigate the effects of mining on soil. The introduced species have spread to other ecosystems resulting in ecological deteriorations. The problem is compounded by hybridization of the species making identification between the native and exotic species difficult. This study investigated the potential of remote sensing in identifying native, non-native and hybrid Tamarix species recorded in South Africa. Leaf- and canopy-level classifications of the species were conducted using field spectroradiometer data that provided two inputs: original hyperspectral data and bands simulated according to Landsat-8, Sentinel-2, SPOT-6 and WorldView-3. The original hyperspectral data yielded high accuracies for leaf- and plot-level discriminations (>90%), while promising accuracies were also obtained using Landsat-8, Sentinel-2 and Worldview-3 simulations (>75%). These findings encourage for investigating the performance of actual space-borne multispectral data in classifying the species. Numéro de notice : A2022-928 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/10106049.2021.1983033 Date de publication en ligne : 27/09/2021 En ligne : https://doi.org/10.1080/10106049.2021.1983033 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102661 [article]

Classification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)  

Public [article]  inApplied geomatics > vol 13 n° 3 (September 2021) . - pp 373 - 387 Titre : Classification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery Type de document : Article/Communication Auteurs : Simbarashe Jombo, Auteur ; Elhadi Adam, Auteur ; John Odindi, Auteur Année de publication : 2021 Article en page(s) : pp 373 - 387 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse d'image orientée objet [Termes IGN] arbre urbain [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] espèce végétale [Termes IGN] image à très haute résolution [Termes IGN] image multibande [Termes IGN] image Worldview [Termes IGN] indice de végétation [Termes IGN] Johannesbourg [Termes IGN] segmentation d'image Résumé : (auteur) Urban trees are valuable in, inter alia, ameliorating air pollution and mitigating the effects associated with urban heat islands. The dearth of tree cover maps is a major challenge for urban planners in the management of urban trees. This work adopts remote sensing approaches to provide urban tree cover maps which can strengthen urban landscape management. Whereas traditional pixel-based classification approaches have been commonly used in image classification, they are not well-suited for urban tree mapping due to their failure to fully explore the image’s spatial and spectral characteristics. Object-based classification techniques produce improved accuracies using additional variables. This study depicts the capability of object-based image analysis (OBIA) in mapping common urban trees using very high-resolution (VHR) WorldView-2 (WV-2) imagery. The study tests the utility of WV-2 bands and other feature variables in the object-based mapping of common urban trees and other land cover classes. Furthermore, the study compares the utility of Support Vector Machine (SVM) and Random Forest (RF) in the object-based mapping of common urban trees and other land cover classes. The results show that the Normalized Difference Vegetation Index (NDVI), NIR 1 and NIR 2 bands were important in the classification of common urban trees and other land cover classes. The RF classifier performed better than SVM, with an overall accuracy of 91.9% as compared to 87.3% for SVM. The results of this study offer insight to urban authorities with knowledge on the segmentation parameters, classification methods and feature variables for mapping urban trees, valuable in urban tree management. Numéro de notice : A2021-624 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s12518-021-00358-3 Date de publication en ligne : 20/01/2021 En ligne : https://doi.org/10.1007/s12518-021-00358-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98248 [article]

Testing the reliability and stability of the internal accuracy assessment of random forest for classifying tree defoliation levels using different validation methods / Samuel Adelabu in Geocarto international, vol 30 n° 7 - 8 (August - September 2015)  

Public [article]  inGeocarto international > vol 30 n° 7 - 8 (August - September 2015) . - pp 810 - 821 Titre : Testing the reliability and stability of the internal accuracy assessment of random forest for classifying tree defoliation levels using different validation methods Type de document : Article/Communication Auteurs : Samuel Adelabu, Auteur ; Onisimo Mutanga, Auteur ; Elhadi Adam, Auteur Année de publication : 2015 Article en page(s) : pp 810 - 821 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] défoliation [Termes IGN] image multibande [Termes IGN] image RapidEye [Termes IGN] méthode fiable Résumé : (Auteur) In this study, the strength and reliability of internal accuracy estimate built in random forest (RF) ensemble classifier was evaluated. Specifically, we compared the reliability of the internal validation methods of RF with independent data-sets of different splitting options for defoliation classification. Furthermore, we set out to statistically validate the best independent split option for image classification using RF and multispectral Rapideye imagery. Results show that the internal accuracy measure yields comparable results with those derived from an independent test data-set. More important, it was observed that the errors produced by the internal validation methods of RF were relatively stable as statistically shown by the lower confidence interval obtained as compared to the independent test data. Results also showed that the 70–30% split option had the lowest mean standard errors (0.2351) and hence highest accuracy when compared to the other split options. The study confirms the reliability and stability of the internal bootstrapping estimate of accuracy built within the random forest algorithm. Numéro de notice : A2015-503 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2014.997303 Date de publication en ligne : 04/02/2015 En ligne : http://www.tandfonline.com/doi/abs/10.1080/10106049.2014.997303 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77420 [article]

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059-2015041	RAB	Revue	Centre de documentation	En réserve L003	Disponible