Descripteur
Termes IGN > géomatique > données localisées
données localiséesSynonyme(s)spatial data ;données géospatiales ;données géographiques données à référence spatialeVoir aussi |
Documents disponibles dans cette catégorie (3470)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review / Sahar S. Matin in Geocarto international, Vol 37 n° 21 ([01/10/2022])
[article]
Titre : Challenges and limitations of earthquake-induced building damage mapping techniques using remote sensing images : A systematic review Type de document : Article/Communication Auteurs : Sahar S. Matin, Auteur ; Biswajeet Pradhan, Auteur Année de publication : 2022 Article en page(s) : pp 6186 - 6212 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] cartographie thématique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] déformation d'édifice
[Termes IGN] détection de changement
[Termes IGN] dommage matériel
[Termes IGN] données lidar
[Termes IGN] image optique
[Termes IGN] image radar moirée
[Termes IGN] secours d'urgence
[Termes IGN] séismeRésumé : (auteur) Assessing the extent and level of building damages is crucial to support post-earthquake rescue and relief activities. There is a large body of literature proposing novel frameworks for automating earthquake-induced building damage mapping using high-resolution remote sensing images. Yet, its deployment in real-world scenarios is largely limited to the manual interpretation of images. Although manual interpretation is costly and labor-intensive, it is preferred over automatic and semi-automatic building damage mapping frameworks such as machine learning and deep learning because of its reliability. Therefore, this review paper explores various automatic and semi-automatic building damage mapping techniques with a quest to understand the pros and cons of different methodologies to narrow the gap between research and practice. Further, the research gaps and opportunities are identified for the future development of real-world scenarios earthquake-induced building damage mapping. This review can serve as a guideline for researchers, decision-makers, and practitioners in the emergency management service domain. Numéro de notice : A2022-719 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2021.1933213 Date de publication en ligne : 07/06/2021 En ligne : https://doi.org/10.1080/10106049.2021.1933213 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101651
in Geocarto international > Vol 37 n° 21 [01/10/2022] . - pp 6186 - 6212[article]Réservation
Réserver ce documentExemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 059-2022211 RAB Revue Centre de documentation En réserve L003 Disponible Correcting laser scanning intensity recorded in a cave environment for high-resolution lithological mapping: A case study of the Gouffre Georges, France / Michaela Nováková in Remote sensing of environment, vol 280 (October 2022)
[article]
Titre : Correcting laser scanning intensity recorded in a cave environment for high-resolution lithological mapping: A case study of the Gouffre Georges, France Type de document : Article/Communication Auteurs : Michaela Nováková, Auteur ; Michal Gallay, Auteur ; Jozef Šupinský, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 113210 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] amélioration du contraste
[Termes IGN] Ariège (09)
[Termes IGN] cartographie géologique
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] filtrage du bruit
[Termes IGN] grotte
[Termes IGN] intensité lumineuse
[Termes IGN] lithologie
[Termes IGN] roche
[Termes IGN] semis de points
[Termes IGN] télémétrie laser terrestreRésumé : (auteur) Active remote sensing by laser scanning (LiDAR) has markedly improved the mapping of a cave environment with an unprecedented level of accuracy and spatial detail. However, the use of laser intensity simultaneously recorded during the scanning of caves remains unexplored despite it having promising potential for lithological mapping as it has been demonstrated by many applications in open-sky conditions. The appropriate use of laser intensity requires calibration and corrections for influencing factors, which are different in caves as opposed to the above-ground environments. Our study presents an efficient and complex workflow to correct the recorded intensity, which takes into consideration the acquisition geometry, micromorphology of the cave surface, and the specific atmospheric influence previously neglected in terrestrial laser scanning. The applicability of the approach is demonstrated on terrestrial LiDAR data acquired in the Gouffre Georges, a cave located in the northern Pyrenees in France. The cave is unique for its geology and lithology allowing for observation, with a spectacular continuity without any vegetal cover, of the contact between marble and lherzolite rocks and tectonic structures that characterize such contact. The overall accuracy of rock surface classification based on the corrected laser intensity was over 84%. The presence of water or a wet surface introduced bias of the intensity values towards lower values complicating the material discrimination. Such conditions have to be considered in applications of the recorded laser intensity in mapping underground spaces. The presented method allows for putting geological observations in an absolute spatial reference frame, which is often very difficult in a cave environment. Thus, laser scanning of the cave geometry assigned with the corrected laser intensity is an invaluable tool to unravel the complexity of such a lithological environment. Numéro de notice : A2022-775 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.rse.2022.113210 Date de publication en ligne : 10/08/2022 En ligne : https://doi.org/10.1016/j.rse.2022.113210 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101807
in Remote sensing of environment > vol 280 (October 2022) . - n° 113210[article]Detecting overmature forests with airborne laser scanning (ALS) / Marc Fuhr in Remote sensing in ecology and conservation, vol 8 n° 5 (October 2022)
[article]
Titre : Detecting overmature forests with airborne laser scanning (ALS) Type de document : Article/Communication Auteurs : Marc Fuhr, Auteur ; Etienne Lalechère, Auteur ; Jean-Matthieu Monnet, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 731 - 743 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] Abies alba
[Termes IGN] âge du peuplement forestier
[Termes IGN] Bootstrap (statistique)
[Termes IGN] canopée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] coefficient de corrélation
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] Fagus sylvatica
[Termes IGN] Picea abies
[Termes IGN] Préalpes (France)
[Termes IGN] semis de points
[Termes IGN] structure d'un peuplement forestierRésumé : (auteur) Building a network of interconnected overmature forests is crucial for the conservation of biodiversity. Indeed, a multitude of plant and animal species depend on forest structural maturity attributes such as very large living trees and deadwood. LiDAR technology has proved to be powerful when assessing forest structural parameters, and it may be a promising way to identify existing overmature forest patches over large areas. We first built an index (IMAT) combining several forest structural maturity attributes in order to characterize the structural maturity of 660 field plots in the French northern Pre-Alps. We then selected or developed LiDAR metrics and applied them in a random forest model designed to predict the IMAT. Model performance was evaluated with the root mean square error of prediction obtained from a bootstrap cross-validation and a Spearman correlation coefficient calculated between observed and predicted IMAT. Predictors were ranked by importance based on the average increase in the squared out-of-bag error when the variable was randomly permuted. Despite a non-negligible RMSEP (0.85 for calibration and validation data combined and 1.26 for validation data alone), we obtained a high correlation (0.89) between the observed and predicted IMAT values, indicating an accurate ranking of the field plots. LiDAR metrics for height (maximum height and height heterogeneity) were among the most important metrics for predicting forest maturity, together with elevation, slope and, to a lesser extent, with metrics describing the distribution of echoes' intensities. Our framework makes it possible to reconstruct a forest maturity gradient and isolate maturity hot spots. Nevertheless, our approach could be considerably strengthened by taking into consideration site fertility, collecting other maturity attributes in the field or developing adapted LiDAR metrics. Including additional spectral or textural metrics from optical imagery might also improve the predictive capacity of the model. Numéro de notice : A2022-880 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1002/rse2.274 Date de publication en ligne : 15/07/2022 En ligne : https://doi.org/10.1002/rse2.274 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102197
in Remote sensing in ecology and conservation > vol 8 n° 5 (October 2022) . - pp 731 - 743[article]Incremental road network update method with trajectory data and UAV remote sensing imagery / Jianxin Qin in ISPRS International journal of geo-information, vol 11 n° 10 (October 2022)
[article]
Titre : Incremental road network update method with trajectory data and UAV remote sensing imagery Type de document : Article/Communication Auteurs : Jianxin Qin, Auteur ; Wenjie Yang, Auteur ; Tao Wu, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 502 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage profond
[Termes IGN] données spatiotemporelles
[Termes IGN] extraction du réseau routier
[Termes IGN] image captée par drone
[Termes IGN] mise à jour de base de données
[Termes IGN] modèle de Markov caché
[Termes IGN] OpenStreetMap
[Termes IGN] réseau routier
[Termes IGN] segmentation
[Termes IGN] trace au solRésumé : (auteur) GPS trajectory and remote sensing data are crucial for updating urban road networks because they contain critical spatial and temporal information. Existing road network updating methods, whether trajectory-based (TB) or image-based (IB), do not integrate the characteristics of both types of data. This paper proposed and implemented an incremental update method for rapid road network checking and updating. A composite update framework for road networks is established, which integrates trajectory data and UAV remote sensing imagery. The research proposed utilizing connectivity between adjacent matched points to solve the problem of updating problematic road segments in networks based on the features of the Hidden Markov Model (HMM) map-matching method in identifying new road segments. Deep learning is used to update the local road network in conjunction with the flexible and high-precision characteristics of UAV remote sensing. Additionally, the proposed method is evaluated against two baseline methods through extensive experiments based on real-world trajectories and UAV remote sensing imagery. The results show that our method has higher extraction accuracy than the TB method and faster updates than the IB method. Numéro de notice : A2022-791 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/ijgi11100502 Date de publication en ligne : 27/09/2022 En ligne : https://doi.org/10.3390/ijgi11100502 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101904
in ISPRS International journal of geo-information > vol 11 n° 10 (October 2022) . - n° 502[article]Monitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT) / Julian Fäth in Journal of Forestry Research, vol 33 n° 5 (October 2022)
[article]
Titre : Monitoring spatiotemporal soil moisture changes in the subsurface of forest sites using electrical resistivity tomography (ERT) Type de document : Article/Communication Auteurs : Julian Fäth, Auteur ; Julius Kunz, Auteur ; Christof Kneisel, Auteur Année de publication : 2022 Article en page(s) : pp 1649 - 1662 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Bavière (Allemagne)
[Termes IGN] changement climatique
[Termes IGN] détection de changement
[Termes IGN] données spatiotemporelles
[Termes IGN] écologie forestière
[Termes IGN] forêt tempérée
[Termes IGN] humidité du sol
[Termes IGN] résistivité
[Termes IGN] sécheresse
[Termes IGN] série temporelle
[Termes IGN] tomographie
[Termes IGN] variation saisonnièreRésumé : (auteur) The effects of drought on tree mortality at forest stands are not completely understood. For assessing their water supply, knowledge of the small-scale distribution of soil moisture as well as its temporal changes is a key issue in an era of climate change. However, traditional methods like taking soil samples or installing data loggers solely collect parameters of a single point or of a small soil volume. Electrical resistivity tomography (ERT) is a suitable method for monitoring soil moisture changes and has rarely been used in forests. This method was applied at two forest sites in Bavaria, Germany to obtain high-resolution data of temporal soil moisture variations. Geoelectrical measurements (2D and 3D) were conducted at both sites over several years (2015–2018/2020) and compared with soil moisture data (matric potential or volumetric water content) for the monitoring plots. The greatest variations in resistivity values that highly correlate with soil moisture data were found in the main rooting zone. Using the ERT data, temporal trends could be tracked in several dimensions, such as the interannual increase in the depth of influence from drought events and their duration, as well as rising resistivity values going along with decreasing soil moisture. The results reveal that resistivity changes are a good proxy for seasonal and interannual soil moisture variations. Therefore, 2D- and 3D-ERT are recommended as comparatively non-laborious methods for small-spatial scale monitoring of soil moisture changes in the main rooting zone and the underlying subsurface of forested sites. Higher spatial and temporal resolution allows a better understanding of the water supply for trees, especially in times of drought. Numéro de notice : A2022-778 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1007/s11676-022-01498-x Date de publication en ligne : 18/06/2022 En ligne : https://doi.org/10.1007/s11676-022-01498-x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101838
in Journal of Forestry Research > vol 33 n° 5 (October 2022) . - pp 1649 - 1662[article]Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products / Ankit Sagar in ISPRS Journal of photogrammetry and remote sensing, vol 192 (October 2022)PermalinkNovel algorithm based on geometric characteristics for tree branch skeleton extraction from LiDAR point cloud / Jie Yang in Forests, vol 13 n° 10 (October 2022)Permalink3D LiDAR aided GNSS/INS integration fault detection, localization and integrity assessment in urban canyons / Zhipeng Wang in Remote sensing, vol 14 n° 18 (September-2 2022)PermalinkForest canopy stratification based on fused, imbalanced and collinear LiDAR and Sentinel-2 metrics / Jakob Wernicke in Remote sensing of environment, vol 279 (September-15 2022)PermalinkThe FIRST model: Spatiotemporal fusion incorrporting spectral autocorrelation / Shuaijun Liu in Remote sensing of environment, vol 279 (September-15 2022)PermalinkAn exploratory assessment of the effectiveness of geomasking methods on privacy protection and analytical accuracy for individual-level geospatial data / Jue Wang in Cartography and Geographic Information Science, Vol 49 n° 5 (September 2022)PermalinkBenchmarking laser scanning and terrestrial photogrammetry to extract forest inventory parameters in a complex temperate forest / Daniel Kükenbrink in International journal of applied Earth observation and geoinformation, vol 113 (September 2022)PermalinkEstimating carbon stocks and biomass expansion factors of urban greening trees using terrestrial laser scanning / Linlin Wu in Forests, vol 13 n° 9 (september 2022)PermalinkGeoscience Knowledge Graph (GeoKG): Development, construction and challenges / Xueying Zhang in Transactions in GIS, vol 26 n° 6 (September 2022)PermalinkA multi-source spatio-temporal data cube for large-scale geospatial analysis / Fan Gao in International journal of geographical information science IJGIS, vol 36 n° 9 (September 2022)Permalink