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Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches / S.M. Hamylton in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)
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Titre : Evaluating techniques for mapping island vegetation from unmanned aerial vehicle (UAV) images: Pixel classification, visual interpretation and machine learning approaches Type de document : Article/Communication Auteurs : S.M. Hamylton, Auteur ; R.H. Morris, Auteur ; R.C. Carvalho, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : n° 102085 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] carte de la végétation
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification pixellaire
[Termes IGN] détection de changement
[Termes IGN] données de terrain
[Termes IGN] image captée par drone
[Termes IGN] Nouvelle-Galles du Sud
[Termes IGN] pesticide
[Termes IGN] réserve naturelle
[Termes IGN] série temporelle
[Termes IGN] surveillance de la végétationRésumé : (auteur) We evaluate three approaches to mapping vegetation using images collected by an unmanned aerial vehicle (UAV) to monitor rehabilitation activities in the Five Islands Nature Reserve, Wollongong (Australia). Between April 2017 and July 2018, four aerial surveys of Big Island were undertaken to map changes to island vegetation following helicopter herbicide sprays to eradicate weeds, including the creeper Coastal Morning Glory (Ipomoea cairica) and Kikuyu Grass (Cenchrus clandestinus). The spraying was followed by a large scale planting campaign to introduce native plants, such as tussocks of Spiny-headed Mat-rush (Lomandra longifolia). Three approaches to mapping vegetation were evaluated, including: (i) a pixel-based image classification algorithm applied to the composite spectral wavebands of the images collected, (ii) manual digitisation of vegetation directly from images based on visual interpretation, and (iii) the application of a machine learning algorithm, LeNet, based on a deep learning convolutional neural network (CNN) for detecting planted Lomandra tussocks. The uncertainty of each approach was assessed via comparison against an independently collected field dataset. Each of the vegetation mapping approaches had a comparable accuracy; for a selected weed management and planting area, the overall accuracies were 82 %, 91 % and 85 % respectively for the pixel based image classification, the visual interpretation / digitisation and the CNN machine learning algorithm. At the scale of the whole island, statistically significant differences in the performance of the three approaches to mapping Lomandra plants were detected via ANOVA. The manual digitisation took a longer time to perform than others. The three approaches resulted in markedly different vegetation maps characterised by different digital data formats, which offered fundamentally different types of information on vegetation character. We draw attention to the need to consider how different digital map products will be used for vegetation management (e.g. monitoring the health individual species or a broader profile of the community). Where individual plants are to be monitored over time, a feature-based approach that represents plants as vector points is appropriate. The CNN approach emerged as a promising technique in this regard as it leveraged spatial information from the UAV images within the architecture of the learning framework by enforcing a local connectivity pattern between neurons of adjacent layers to incorporate the spatial relationships between features that comprised the shape of the Lomandra tussocks detected. Numéro de notice : A2020-716 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102085 Date de publication en ligne : 03/03/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102085 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96287
in International journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102085[article]Improved depth estimation for occlusion scenes using a light-field camera / Changkun Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)
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Titre : Improved depth estimation for occlusion scenes using a light-field camera Type de document : Article/Communication Auteurs : Changkun Yang, Auteur ; Zhaoqin Liu, Auteur ; Kaichang Di, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 443-456 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] caméra numérique
[Termes IGN] classification pixellaire
[Termes IGN] détection de partie cachée
[Termes IGN] disparité
[Termes IGN] effet de profondeur cinétique
[Termes IGN] lentille
[Termes IGN] méthode de centrage
[Termes IGN] rayonnement lumineux
[Termes IGN] reconstruction 3DRésumé : (Auteur) With the development of light-field imaging technology, depth estimation using light-field cameras has become a hot topic in recent years. Even through many algorithms have achieved good performance for depth estimation using light-field cameras, removing the influence of occlusion, especially multi-occlusion, is still a challenging task. The photo-consistency assumption does not hold in the presence of occlusions, which makes most depth estimation of light-field imaging unreliable. In this article, a novel method to handle complex occlusion in depth estimation of light-field imaging is proposed. The method can effectively identify occluded pixels using a refocusing algorithm, accurately select unoccluded views using the adaptive unoccluded-view identification algorithm, and then improve the depth estimation by computing the cost volumes in the unoccluded views. Experimental results demonstrate the advantages of our proposed algorithm compared with conventional state-of-the art algorithms on both synthetic and real light-field data sets. Numéro de notice : A2020-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.7.443 Date de publication en ligne : 01/07/2020 En ligne : https://doi.org/10.14358/PERS.86.7.443 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95430
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 7 (July 2020) . - pp 443-456[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2020071 SL Revue Centre de documentation Revues en salle Disponible A novel framework based on polarimetric change vectors for unsupervised multiclass change detection in dual-pol intensity SAR images / David Pirrone in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)
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Titre : A novel framework based on polarimetric change vectors for unsupervised multiclass change detection in dual-pol intensity SAR images Type de document : Article/Communication Auteurs : David Pirrone, Auteur ; Francesca Bovolo, Auteur ; Lorenzo Bruzzone, Auteur Année de publication : 2020 Article en page(s) : pp 4780 - 4795 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] classification automatique
[Termes IGN] classification non dirigée
[Termes IGN] coordonnées polaires
[Termes IGN] détection de changement
[Termes IGN] image multitemporelle
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] méthode des vecteurs de changement
[Termes IGN] polarimétrie radar
[Termes IGN] radar à antenne synthétiqueRésumé : (auteur) Change detection (CD) is a crucial topic in many remote sensing applications. In the recent years, satellite polarimetric synthetic aperture radar (PolSAR) systems (e.g., the Sentinel-1 constellation) became a suitable tool for multitemporal monitoring due to the regular acquisitions with a short revisit time in different polarimetric channels. Methods for CD in PolSAR data mainly focus on binary CD (i.e., they provide information about the presence/absence of change only), whereas the polarimetric enhanced information provides multiple features that can be exploited for performing multiclass CD. In this article, we introduce a novel framework for the characterization of multitemporal changes in dual-polarimetric data. The framework is based on the definition of polarimetric change vectors (PCVs) and their representation in a polar coordinate system. PCVs allow characterizing and, thus, to separate multiclass changes in terms of target properties of the single-time scenes and the scattering theory. The proposed model is used to: 1) derive the statistical behaviors of change and no change classes in PolSAR multitemporal images; 2) design an automatic and unsupervised strategy to estimate the optimal number of changes; and 3) distinguish no change from change classes and the kinds of change from each other. An experimental analysis has been conducted on three multitemporal PolSAR data sets having different complexities in terms of number and kinds of change classes. The results confirm the effectiveness of the proposed approach and the better performance with respect to both specific techniques for CD in dual-pol SAR data and a general multiclass CD method, not designed for PolSAR data. Numéro de notice : A2020-390 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2966865 Date de publication en ligne : 04/02/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2966865 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95373
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 7 (July 2020) . - pp 4780 - 4795[article]Rethinking error estimations in geospatial data: the correct way to determine product accuracy / Qassim Abdullah in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)
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Titre : Rethinking error estimations in geospatial data: the correct way to determine product accuracy Type de document : Article/Communication Auteurs : Qassim Abdullah, Auteur Année de publication : 2020 Article en page(s) : pp 397-403 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Topographie moderne
[Termes IGN] cartographie numérique
[Termes IGN] détection d'erreur
[Termes IGN] données localisées
[Termes IGN] ellipsoïde (géodésie)
[Termes IGN] estimation de précision
[Termes IGN] nivellement direct
[Termes IGN] point d'appui
[Termes IGN] réalité de terrain
[Termes IGN] système de référence géodésique
[Termes IGN] système de référence localRésumé : (Auteur) Numéro de notice : A2020-380 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.7.397 Date de publication en ligne : 01/07/2020 En ligne : https://doi.org/10.14358/PERS.86.7.397 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95425
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 7 (July 2020) . - pp 397-403[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2020071 SL Revue Centre de documentation Revues en salle Disponible Roles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects / Jike Chen in International journal of applied Earth observation and geoinformation, vol 89 (July 2020)
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Titre : Roles of horizontal and vertical tree canopy structure in mitigating daytime and nighttime urban heat island effects Type de document : Article/Communication Auteurs : Jike Chen, Auteur ; Shuanggen Jin, Auteur ; Peijun Du, Auteur Année de publication : 2020 Article en page(s) : n° 102060 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] arbre urbain
[Termes IGN] canopée
[Termes IGN] carte de la végétation
[Termes IGN] couvert forestier
[Termes IGN] données lidar
[Termes IGN] ilot thermique urbain
[Termes IGN] modèle numérique de terrain
[Termes IGN] Nankin (Kiangsou)
[Termes IGN] occupation du sol
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] température au solRésumé : (auteur) The urban heat island (UHI) is increasingly recognized as a serious, worldwide problem because of urbanization and climate change. Urban vegetation is capable of alleviating UHI and improving urban environment by shading together with evapotranspiration. While the impacts of abundance and spatial configuration of vegetation on land surface temperature (LST) have been widely examined, very little attention has been paid to the role of vertical structure of vegetation in regulating LST. In this study, we investigated the relationships between horizontal/vertical structure characteristics of urban tree canopy and LST as well as diurnal divergence in Nanjing City, China, with the help of high resolution vegetation map, Light Detection and Ranging (LiDAR) data and various statistical analysis methods. The results indicated that composition, configuration and vertical structure of tree canopy were all significantly related to both daytime LST and nighttime LST. Tree canopy showed stronger influence on LST during the day than at night. Note that the contribution of composition of tree canopy to explaining spatial heterogeneity of LST, regardless of day and night, was the highest, followed by vertical structure and configuration. Combining composition, configuration and vertical structure of tree canopy can take advantage of their respective advantages, and best explain variation in both daytime LST and nighttime LST. As for the independent importance of factors affecting spatial variation of LST, percent cover of tree canopy (PLAND), mean tree canopy height (TH_Mean), amplitude of tree canopy height (TA) and patch cohesion index (COHESION) were the most influential during the day, while the most important variables were PLAND, maximum height of tree canopy (TH_Max), variance of tree canopy height (TH_SD) and COHESION at night. This research extends our understanding of the impacts of urban trees on the UHI effect from the horizontal to three-dimensional space. In addition, it may offer sustainable and effective strategies for urban designers and planners to cope with increasing temperature. Numéro de notice : A2020-715 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2020.102060 Date de publication en ligne : 25/02/2020 En ligne : https://doi.org/10.1016/j.jag.2020.102060 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96285
in International journal of applied Earth observation and geoinformation > vol 89 (July 2020) . - n° 102060[article]Semi-automatic identification of submarine pipelines with synthetic aperture sonar Images / Victor Hugo Fernandes in Marine geodesy, Vol 43 n° 4 (July 2020)
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