Centre de documentation
scientifique

Generic rule-sets for automated detection of urban tree species from very high-resolution satellite data / Razieh Shojanoori in Geocarto international, vol 33 n° 4 (April 2018)  

Public [article]  inGeocarto international > vol 33 n° 4 (April 2018) . - pp 357 - 374 Titre : Generic rule-sets for automated detection of urban tree species from very high-resolution satellite data Type de document : Article/Communication Auteurs : Razieh Shojanoori, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Shattri Bin Mansor, Auteur ; et al., Auteur Année de publication : 2018 Article en page(s) : pp 357 - 374 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse d'image orientée objet [Termes IGN] arbre (flore) [Termes IGN] arbre urbain [Termes IGN] base de règles [Termes IGN] détection d'arbres [Termes IGN] image Worldview [Termes IGN] Malaisie [Termes IGN] traitement d'image [Termes IGN] zone urbaine Résumé : (Auteur) The sustainable management and monitoring of urban forests is an important activity in the urbanized world, and operational approaches require information about the status of urban trees to determine the best strategy. One limitation in urban forest studies is the detection and discrimination of tree species using limited training data. Thus, this study focuses on developing generic rule sets from high-resolution WorldView-2 imagery in conjunction with spectral, spatial, colour and textural information for automated urban tree species detection. The object-based image analysis and its combination with statistical analysis of object features is utilized for this purpose. Results of attribute selection indicated that from 55 attributes, only 26 were useful to discriminate urban tree species, namely Messua ferrea L., Samanea saman and Casuarina sumatrana. Finally, the high overall accuracy, approximately 86.87% with kappa of 0.75 confirmed the transferability of the generic model. Numéro de notice : A2018-046 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2016.1265593 En ligne : https://doi.org/10.1080/10106049.2016.1265593 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89268 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2018021	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Influence of tree species complexity on discrimination performance of vegetation indices / Azadeh Ghiyamat in European journal of remote sensing, vol 49 n° 1 (2016)  

Public [article]  inEuropean journal of remote sensing > vol 49 n° 1 (2016) . - pp 15 - 37 Titre : Influence of tree species complexity on discrimination performance of vegetation indices Type de document : Article/Communication Auteurs : Azadeh Ghiyamat, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Abdul Rashid Mohamed Shariff, Auteur Année de publication : 2016 Article en page(s) : pp 15 - 37 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] analyse de mélange spectral d’extrémités multiples [Termes IGN] analyse discriminante [Termes IGN] espèce végétale [Termes IGN] image aérienne [Termes IGN] image hyperspectrale [Termes IGN] indice de végétation [Termes IGN] information complexe [Termes IGN] Pinus nigra corsicana [Termes IGN] Pinus sylvestris [Termes IGN] test de performance Résumé : (auteur) Performance of different vegetation indices (VIs) in combination with single- and multipleendmember (SEM and MEM) for discriminating Corsican and Scots pines with different ages and Broadleaves tree species is demonstrated by using an airborne hyperspectral data. The analysis is performed in three different complexity levels. The results show by increasing tree species complexity, overall accuracy significantly reduced. An overall accuracy up to 90% is obtained from the first category with the least complexity; however, it is reduced to 55% in the third category with the highest complexity. By employing MEM, performance of normalized difference vegetation index (NDVI) is increased by 10%. Numéro de notice : A2016-834 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.5721/EuJRS20164902 En ligne : http://dx.doi.org/10.5721/EuJRS20164902 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82723 [article]

Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery / Biswajeet Pradhan in IEEE Transactions on geoscience and remote sensing, vol 54 n° 3 (March 2016)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 54 n° 3 (March 2016) . - pp 1610 - 1622 Titre : Data fusion technique using wavelet transform and Taguchi methods for automatic landslide detection from airborne laser scanning data and QuickBird satellite imagery Type de document : Article/Communication Auteurs : Biswajeet Pradhan, Auteur ; Mustafa Neamah Jebur, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Mahyat Shafapour Tehrany, Auteur Année de publication : 2016 Article en page(s) : pp 1610 - 1622 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] carte thématique [Termes IGN] classification dirigée [Termes IGN] données lidar [Termes IGN] effondrement de terrain [Termes IGN] fusion d'images [Termes IGN] image Quickbird [Termes IGN] Malaisie [Termes IGN] précision des données [Termes IGN] transformation en ondelettes Résumé : (Auteur) Landslide mapping is indispensable for efficient land use management and planning. Landslide inventory maps must be produced for various purposes, such as to record the landslide magnitude in an area and to examine the distribution, types, and forms of slope failures. The use of this information enables the study of landslide susceptibility, hazard, and risk, as well as of the evolution of landscapes affected by landslides. In tropical countries, precipitation during the monsoon season triggers hundreds of landslides in mountainous regions. The preparation of a landslide inventory in such regions is a challenging task because of rapid vegetation growth. Thus, enhancing the proficiency of landslide mapping using remote sensing skills is a vital task. Various techniques have been examined by researchers. This study uses a robust data fusion technique that integrates high-resolution airborne laser scanning data (LiDAR) with high-resolution QuickBird satellite imagery (2.6-m spatial resolution) to identify landslide locations in Bukit Antarabangsa, Ulu Klang, Malaysia. This idea is applied for the first time to identify landslide locations in an urban environment in tropical areas. A wavelet transform technique was employed to achieve data fusion between LiDAR and QuickBird imagery. An object-oriented classification method was used to differentiate the landslide locations from other land use/covers. The Taguchi technique was employed to optimize the segmentation parameters, whereas the rule-based technique was used for object-based classification. In addition, to assess the impact of fusion in classification and landslide analysis, the rule-based classification method was also applied on original QuickBird data which have not been fused. Landslide locations were detected, and the confusion matrix was used to examine the proficiency and reliability of the results. The achieved overall accuracy and kappa coefficient were 90.06% and 0.84, respectively, for fused data. Mor- over, the acquired producer and user accuracies for landslide class were 95.86% and 95.32%, respectively. Results of the accuracy assessment for QuickBird data before fusion showed 65.65% and 0.59 for overall accuracy and kappa coefficient, respectively. It revealed that fusion made a significant improvement in classification results. The direction of mass movement was recognized by overlaying the final landslide classification map with LiDAR-derived slope and aspect factors. Results from the tested site in a hilly area showed that the proposed method is easy to implement, accurate, and appropriate for landslide mapping in a tropical country, such as Malaysia. Numéro de notice : A2016-127 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2015.2484325 En ligne : http://dx.doi.org/10.1109/TGRS.2015.2484325 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80008 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
065-2016031	SL	Revue	Centre de documentation	Revues en salle	Disponible

Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery / Mustafa Neamah Jebur in Geocarto international, vol 29 n° 7 - 8 (November - December 2014)  

Public [article]  inGeocarto international > vol 29 n° 7 - 8 (November - December 2014) . - pp 792 - 806 Titre : Per-pixel and object-oriented classification methods for mapping urban land cover extraction using SPOT 5 imagery Type de document : Article/Communication Auteurs : Mustafa Neamah Jebur, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur ; Biswajeet Pradhan, Auteur ; et al., Auteur Année de publication : 2014 Article en page(s) : pp 792 - 806 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] cartographie urbaine [Termes IGN] classification dirigée [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] extraction automatique [Termes IGN] image SPOT 5 [Termes IGN] utilisation du sol Résumé : (Auteur) To have sustainable management and proper decision-making, timely acquisition and analysis of surface features are necessary. Traditional pixel-based analysis is the popular way to extract different categories, but it is not comparable by the achievements that can be achieved through the object-based method that uses the additional characteristics of features in the process of classification. In this paper, three types of classification were used to classify SPOT 5 satellite image in mapping land cover; Support vector machine (SVM) pixel-based, SVM object-based and Decision Tree (DT) pixel-based classification. Normalised Difference Vegetation Index and the brightness value of two infrared bands (NIR and SWIR) were used in manually developed DT classification. The classification of the SVM (pixel based) was generated using the selected groups of pixels that represent the selected features. In addition, the SVM (object based) was implemented by using radial-based function kernel. The classified features were oil palm, rubber, urban area, soil, water and other vegetation. The study found that the overall classification of the DT was the lowest at 69.87% while those of SVM (pixel based) and SVM (object based) were 76.67 and 81.25%, respectively. Numéro de notice : A2014-468 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2013.848944 En ligne : https://doi.org/10.1080/10106049.2013.848944 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=74045 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2014041	RAB	Revue	Centre de documentation	En réserve L003	Disponible

Development of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery / Alireza Hamedianfar in Geocarto international, vol 29 n° 3 - 4 (June - July 2014)  

Public [article]  inGeocarto international > vol 29 n° 3 - 4 (June - July 2014) . - pp. 268 - 292 Titre : Development of fuzzy rule-based parameters for urban object-oriented classification using very high resolution imagery Type de document : Article/Communication Auteurs : Alireza Hamedianfar, Auteur ; Helmi Zulhaidi Mohd Shafri, Auteur Année de publication : 2014 Article en page(s) : pp. 268 - 292 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] classification floue [Termes IGN] classification orientée objet [Termes IGN] image Worldview [Termes IGN] Malaisie [Termes IGN] zone urbaine Résumé : (Auteur) Urban areas consist of spectrally and spatially heterogeneous features. Advanced information extraction techniques are needed to handle high resolution imageries in providing detailed information for urban planning applications. This study was conducted to identify a technique that accurately maps impervious and pervious surfaces from WorldView-2 (WV-2) imagery. Supervised per-pixel classification algorithms including Maximum Likelihood and Support Vector Machine (SVM) were utilized to evaluate the capability of spectral-based classifiers to classify urban features. Object-oriented classification was performed using supervised SVM and fuzzy rule-based approach to add spatial and texture attributes to spectral information. Supervised object-oriented SVM achieved 82.80% overall accuracy which was the better accuracy compared to supervised per-pixel classifiers. Classification based on the proposed fuzzy rule-based system revealed satisfactory output compared to other classification techniques with an overall accuracy of 87.10% for pervious surfaces and an overall accuracy of 85.19% for impervious surfaces. Numéro de notice : A2014-339 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2012.760006 En ligne : https://doi.org/10.1080/10106049.2012.760006 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73707 [article]

Exemplaires(1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
059-2014021	RAB	Revue	Centre de documentation	En réserve L003	Disponible