Descripteur
Documents disponibles dans cette catégorie (734)
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
Etendre la recherche sur niveau(x) vers le bas
Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? / Fabian E. Fassnacht in Forestry, an international journal of forest research, vol 90 n° 5 (December 2017)
![]()
[article]
Titre : Estimating stand density, biomass and tree species from very high resolution stereo-imagery – towards an all-in-one sensor for forestry applications? Type de document : Article/Communication Auteurs : Fabian E. Fassnacht, Auteur ; Daniel Mangold, Auteur ; Jannika Schäfer, Auteur ; Markus Immitzer, Auteur Année de publication : 2017 Article en page(s) : pp 613 - 631 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse comparative
[Termes IGN] biomasse forestière
[Termes IGN] densité de la végétation
[Termes IGN] données lidar
[Termes IGN] espèce végétale
[Termes IGN] image à très haute résolution
[Termes IGN] image aérienne
[Termes IGN] inventaire forestier (techniques et méthodes)
[Vedettes matières IGN] Inventaire forestierRésumé : (Auteur) The estimation of various forest inventory attributes from high spatial resolution airborne remote sensing data has been widely examined and proved to be successful at the experimental level. Nevertheless, the operational use of these data in automated procedures to support forest inventories and forest management is still limited to a small number of cases. The reasons for this are high data costs, limited availability of remote sensing data over large areas and resistance from practitioners. In this review the main aim is to stimulate debate about spaceborne very high resolution stereo-imagery (VHRSI) as an alternative to airborne remote sensing data by presenting: (1) a case study on the retrieval of stand density, aboveground biomass and tree species using a set of easy-to-calculate variables obtained from VHRSI data combined with image processing and nonparametric classification and modelling approaches; and (2) the results of an expert opinion survey on the potential of VHRSI as compared with Light Detection and Ranging (LiDAR), hyperspectral and airborne digital imagery to derive a range of forest inventory attributes. In the case study, stand density was estimated with r² = 0.71 and RMSE = 156 trees (rel./norm. RMSE = 24.9 per cent/12.4 per cent), biomass with r² = 0.64 and RMSE of 36.7 t/ha (rel./norm. RMSE = 20.0 per cent/12.8 per cent) while tree species classifications with five species reached overall accuracies of 84.2 per cent (kappa = 0.81). These results were comparable to earlier studies in the same test site, obtained with more expensive airborne acquisitions. Expert opinions were more diverse for VHRSI and aerial photographs (Shannon index values of 0.94 and 0.97) than for LiDAR and hyperspectral data (Shannon index values 0.69 and 0.88). In our opinion, this reflects the current state-of-the-art in the application of VHRSI for automatically retrieving forest inventory attributes. The number of studies using these data is still limited, and the full potential of these datasets is not yet completely explored. Compared with LiDAR and hyperspectral data, which both mostly received high scores for forest inventory products matching the sensor systems’ strengths, VHRSI and aerial photographs received more homogeneous scores indicating their potential as multi-purpose instruments to collect forest inventory information. In summary, considering the simpler acquisition, reasonable price and the comparably easy data format and handling of VHRSI compared with other sensor types, we recommend further research on the application of these data for supporting operational forest inventories. Numéro de notice : A2017-902 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1093/forestry/cpx014 En ligne : https://doi.org/10.1093/forestry/cpx014 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93196
in Forestry, an international journal of forest research > vol 90 n° 5 (December 2017) . - pp 613 - 631[article]High-resolution aerial image labeling with convolutional neural networks / Emmanuel Maggiori in IEEE Transactions on geoscience and remote sensing, vol 55 n° 12 (December 2017)
![]()
[article]
Titre : High-resolution aerial image labeling with convolutional neural networks Type de document : Article/Communication Auteurs : Emmanuel Maggiori, Auteur ; Yuliya Tarabalka, Auteur ; Guillaume Charpiat, Auteur ; Pierre Alliez, Auteur Année de publication : 2017 Article en page(s) : pp 7092 - 7103 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] image aérienne
[Termes IGN] indexation sémantique
[Termes IGN] inférence sémantique
[Termes IGN] réseau neuronal convolutifRésumé : (Auteur) The problem of dense semantic labeling consists in assigning semantic labels to every pixel in an image. In the context of aerial image analysis, it is particularly important to yield high-resolution outputs. In order to use convolutional neural networks (CNNs) for this task, it is required to design new specific architectures to provide fine-grained classification maps. Many dense semantic labeling CNNs have been recently proposed. Our first contribution is an in-depth analysis of these architectures. We establish the desired properties of an ideal semantic labeling CNN, and assess how those methods stand with regard to these properties. We observe that even though they provide competitive results, these CNNs often underexploit properties of semantic labeling that could lead to more effective and efficient architectures. Out of these observations, we then derive a CNN framework specifically adapted to the semantic labeling problem. In addition to learning features at different resolutions, it learns how to combine these features. By integrating local and global information in an efficient and flexible manner, it outperforms previous techniques. We evaluate the proposed framework and compare it with state-of-the-art architectures on public benchmarks of high-resolution aerial image labeling. Numéro de notice : A2017-769 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2017.2740362 En ligne : https://doi.org/10.1109/TGRS.2017.2740362 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88808
in IEEE Transactions on geoscience and remote sensing > vol 55 n° 12 (December 2017) . - pp 7092 - 7103[article]Stand-level wind damage can be assessed using diachronic photogrammetric canopy height models / Jean-Pierre Renaud in Annals of Forest Science, vol 74 n° 4 (December 2017)
![]()
[article]
Titre : Stand-level wind damage can be assessed using diachronic photogrammetric canopy height models Type de document : Article/Communication Auteurs : Jean-Pierre Renaud , Auteur ; Cédric Vega
, Auteur ; Sylvie Durrieu, Auteur ; Jonathan Lisein
, Auteur ; Magnussen, Steen, Auteur ; Philippe Lejeune, Auteur ; Meriem Fournier, Auteur
Année de publication : 2017 Projets : FOR-WIND / Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse diachronique
[Termes IGN] appariement dense
[Termes IGN] dommage matériel
[Termes IGN] hauteur des arbres
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] photogrammétrie
[Termes IGN] placette d'échantillonnage
[Termes IGN] semis de points
[Termes IGN] tempête
[Termes IGN] volume en bois
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Key message : Diachronic photogrammetric canopy height models can be used to quantify at a fine scale changes in dominant height and wood volume following storms. The regular renewal of aerial surveys makes this approach appealing for monitoring forest changes.
Context : The increasing availability of aerial photographs and the development of dense matching algorithms open up new possibilities to assess the effects of storm events on forest canopies.
Aims : The objective of this research is to assess the potential of diachronic canopy height models derived from photogrammetric point clouds (PCHM) to quantify changes in dominant height and wood volume of a broadleaved forest following a major storm.
Methods : PCHMs derived from aerial photographs acquired before and after a storm event were calibrated using 25 field plots to estimate dominant height and volume using various modeling approaches. The calibrated models were combined with a reference damage maps to estimate both the within-stand damage variability, and the amount of volume impacted.
Results : Dominant height was predicted with a root mean squared error (RMSE) of 4%, and volume with RMSEs ranging from 24 to 32% according to the type of model. The volume impacted by storm was in the range of 42–76%. Overall, the maps of dominant height changes provided more details about within-stand damage variability than conventional photointerpretation do.
Conclusion : The study suggests a promising potential for exploiting PCHM in pursuit of a rapid localization and quantification of wind-throw damages, given an adapted sampling design to calibrate models.Numéro de notice : A2017-733 Affiliation des auteurs : LIF+Ext (2012-2019) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-017-0669-3 En ligne : https://doi.org/10.1007/s13595-017-0669-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88546
in Annals of Forest Science > vol 74 n° 4 (December 2017)[article]Cartographie de la vulnérabilité des bâtiments au risque sismique / Valerio Baiocchi in Géomatique expert, n° 119 (novembre - décembre 2017)
[article]
Titre : Cartographie de la vulnérabilité des bâtiments au risque sismique Type de document : Article/Communication Auteurs : Valerio Baiocchi, Auteur ; Donatella Dominici., Auteur ; Massimo Guarascio, Auteur ; Mara Lombardi, Auteur ; F. Vatore, Auteur Année de publication : 2017 Article en page(s) : pp 31 - 35 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] Abruzzes
[Termes IGN] analyse multiéchelle
[Termes IGN] classification
[Termes IGN] construction
[Termes IGN] données de terrain
[Termes IGN] données ouvertes
[Termes IGN] image aérienne
[Termes IGN] risque naturel
[Termes IGN] séisme
[Termes IGN] vulnérabilitéRésumé : [Introduction] Dans cet article, nous allons montrer comment l'utilisation de logiciels Open Source et de bases de données Open Data permet d'estimer le risque sismique auquel chaque bâtiment situé dans une zone à risque est exposé. Remarquons, en premier lieu, qu'une série de réglementations nationales ont rendu les normes de construction des bâtiments en brique et béton de plus en plus strictes. Il serait donc intéressant d'essayer de corréler la mise en oeuvre de ces normes et les dommages subis en situation de séisme. [...] Numéro de notice : A2017-772 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88826
in Géomatique expert > n° 119 (novembre - décembre 2017) . - pp 31 - 35[article]Réservation
Réserver ce documentExemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 265-2017061 RAB Revue Centre de documentation En réserve L003 Disponible IFN-001-P002007 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt Changement climatique et risque inondation / William Halbecq in Géomatique expert, n° 119 (novembre - décembre 2017)
[article]
Titre : Changement climatique et risque inondation Type de document : Article/Communication Auteurs : William Halbecq, Auteur ; Nicolas Bauduceau, Auteur ; Camille Rossi, Organisateur de réunion Année de publication : 2017 Article en page(s) : pp 36 - 43 Note générale : Entretien organisé par Business Geographics Langues : Français (fre) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] cartographie dynamique
[Termes IGN] changement climatique
[Termes IGN] crue
[Termes IGN] données lidar
[Termes IGN] enjeu
[Termes IGN] erreur de classification
[Termes IGN] historique des données
[Termes IGN] image aérienne
[Termes IGN] inondation
[Termes IGN] modélisation spatiale
[Termes IGN] photo-interprétation
[Termes IGN] plan de prévention des risques
[Termes IGN] précision des données
[Termes IGN] risque naturel
[Termes IGN] submersion marine
[Termes IGN] système d'information géographiqueRésumé : (Auteur) William Halbecq et Nicolas Bauduceau, experts en risques, discutent de la réalité du changement climatique et ce que cela implique pour les risques de crues et de submersion marine. Numéro de notice : A2017-773 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88827
in Géomatique expert > n° 119 (novembre - décembre 2017) . - pp 36 - 43[article]Réservation
Réserver ce documentExemplaires(2)
Code-barres Cote Support Localisation Section Disponibilité 265-2017061 RAB Revue Centre de documentation En réserve L003 Disponible IFN-001-P002007 PER Revue Nogent-sur-Vernisson Salle périodiques Exclu du prêt Automatic shadow detection in aerial and terrestrial images / Vander Luis de Souza Freitas in Boletim de Ciências Geodésicas, vol 23 n° 4 (oct - dec 2017)
![]()
PermalinkEfficient structure from motion for oblique UAV images based on maximal spanning tree expansion / San Jiang in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
PermalinkHyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables / Sakari Tuominen in Silva fennica, vol 51 n° 5 (2017)
PermalinkRegistration of images to Lidar and GIS data without establishing explicit correspondences / Gabor Barsai in Photogrammetric Engineering & Remote Sensing, PERS, vol 83 n° 10 (October 2017)
PermalinkDocumentation of heritage buildings using close-range UAV images: dense matching issues, comparison and case studies / Arnadi Murtiyoso in Photogrammetric record, vol 32 n° 159 (September 2017)
PermalinkEstudio de precision en la aerotriangulacion de bloques de imagenes obtenidas con UAV / Miguel Angel Lopez Gonzalez in Mapping : Teledetección, medio ambiante, cartografía, sistemas de información geográfica, vol 26 n° 185 (septembrie - octubre 2017)
![]()
PermalinkA higher order conditional random field model for simultaneous classification of land cover and land use / Lena Albert in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)
PermalinkImage matching as a data source for forest inventory – Comparison of semi-global matching and next-generation automatic terrain extraction algorithms in a typical managed boreal forest environment / Mari Kukkonen in International journal of applied Earth observation and geoinformation, vol 60 (August 2017)
PermalinkImproving Finnish multi-source national forest inventory by 3D aerial imaging / Sakari Tuominen in Silva fennica, vol 51 n° 4 (2017)
PermalinkLearning and transferring deep joint spectral–spatial features for hyperspectral classification / Jingxiang Yang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 8 (August 2017)
Permalink