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Exploring the relationship between the 2D/3D architectural morphology and urban land surface temperature based on a boosted regression tree: A case study of Beijing, China / Zhen Li in Sustainable Cities and Society, vol 78 (March 2022)
[article]
Titre : Exploring the relationship between the 2D/3D architectural morphology and urban land surface temperature based on a boosted regression tree: A case study of Beijing, China Type de document : Article/Communication Auteurs : Zhen Li, Auteur ; Dan Hu, Auteur Année de publication : 2022 Article en page(s) : n° 103392 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] Bâti-3D
[Termes IGN] classification et arbre de régression
[Termes IGN] corrélation
[Termes IGN] données localisées 2D
[Termes IGN] hauteur du bâti
[Termes IGN] ilot thermique urbain
[Termes IGN] image Landsat-OLI
[Termes IGN] milieu urbain
[Termes IGN] morphologie urbaine
[Termes IGN] Pékin (Chine)
[Termes IGN] saison
[Termes IGN] température au solRésumé : (auteur) With rapid urbanization, urban three-dimensional morphology and its ecological effects have received more attention. However, thorough investigations into the multiple scale impact of the 2D/3D architectural morphology on urban land surface temperature (LST) remain limited. Taking Beijing as a case study area, we quantified the contributions of the 2D/3D architectural morphology indicators and revealed their marginal effects on multiple scales using the boosted regression trees (BRT) method. The results showed that (1) the building coverage ratio and building height were the most significant factors influencing the LST across all spatial scales and seasons, (2) the 3D shape index, 3D fractal, and 3D adjacency were found to be influential factors, with sum contributions varying from 6.0% to 37.7%, and (3) in summer, the 3D shape index showed a stepwise negative correlation with the LST. The 3D fractal and 3D adjacency exhibited both positive and negative correlations with the LST. When the spatial scale was 240 m, the regulation amplitudes for the 3D shape index, 3D fractal, and 3D adjacency were 2.0°C, 1.0°C and 1.0°C, respectively. These findings provide quantitative insights that can be used to improve urban thermal environments and achieve sustainable urban development by adjusting architectural morphology. Numéro de notice : A2022-242 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.scs.2021.103392 Date de publication en ligne : 28/12/2021 En ligne : https://doi.org/10.1016/j.scs.2021.103392 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100169
in Sustainable Cities and Society > vol 78 (March 2022) . - n° 103392[article]IGN, changer d'échelle ! / Jean-Pierre Maillard in XYZ, n° 170 (mars 2022)
[article]
Titre : IGN, changer d'échelle ! Type de document : Article/Communication Auteurs : Jean-Pierre Maillard, Auteur Année de publication : 2022 Article en page(s) : pp 10-11 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] carte thématique
[Termes IGN] données localisées numériques
[Termes IGN] géovisualisation
[Termes IGN] Institut national de l'information géographique et forestière (France)
[Termes IGN] transition écologiqueRésumé : (Auteur) Le 24 novembre 2021, l’institut national de l’information géographique et forestière (IGN) a présenté à ses partenaires institutionnels, industriels et citoyens les premières conclusions de la concertation initiée en mai 2021 sur un projet “géo-communs, avançons ensemble !”, menée en lien avec un ensemble d’acteurs de la communauté géomatique. Réunis dans les murs de Ground Control, l’endroit à la mode du 12ème arrondissement de Paris qui se présente comme un lieu de vie culturel, indépendant et engagé où l’on peut nourrir le corps et l’esprit. Les participants ont été accueillis par Mme Emmanuelle Prada-Bordenave, présidente du conseil d’administration de l’IGN, qui a introduit la rencontre en déclarant que l’institut a engagé sa mue et la recherche de la souveraineté numérique. Puis M. Sébastien Soriano, directeur général, a présenté les actions entreprises déclinées sous forme de chantiers et invité plusieurs intervenants à exprimer leurs points de vue sur différents sujets en relation avec les problématiques tels le biomimétisme ou la carte de France de la nature sauvage. Numéro de notice : A2022-222 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100186
in XYZ > n° 170 (mars 2022) . - pp 10-11[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 112-2022011 RAB Revue Centre de documentation En réserve L003 Disponible LiDAR-based method for analysing landmark visibility to pedestrians in cities: case study in Kraków, Poland / Krystian Pyka in International journal of geographical information science IJGIS, vol 36 n° 3 (March 2022)
[article]
Titre : LiDAR-based method for analysing landmark visibility to pedestrians in cities: case study in Kraków, Poland Type de document : Article/Communication Auteurs : Krystian Pyka, Auteur ; Radoslaw Piskorski, Auteur ; Aleksandra Jasińska, Auteur Année de publication : 2022 Article en page(s) : pp 476 - 495 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse visuelle
[Termes IGN] canyon urbain
[Termes IGN] Cracovie (Pologne)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle numérique de surface
[Termes IGN] paysage urbain
[Termes IGN] piéton
[Termes IGN] point de repère
[Termes IGN] scène urbaine
[Termes IGN] semis de points
[Termes IGN] visibilité (optique)
[Termes IGN] visionRésumé : (auteur) We propose a method for analysing landmark visibility from a pedestrian’s perspective. A case study is performed in Kraków, a city with many architectural monuments, where airborne LiDAR is used to model both buildings and urban greenery. The proposed method involves preliminary and detailed stages. The preliminary stage entails an inverse analysis (I–Vis) that departs from the typical visibility analysis to enable the use of landmarks as observers instead of targets. I–Vis results in paths with high landmark visibility. The detailed stage involves the use of a virtual panorama (V-Pan) to determine the visual exposure of the landmarks. Landmarks considered visible by I–Vis are generally consistent with landmarks identified by V-Pan. Discrepancies occur when trees appear in the near field-of-view. In addition, the accuracy of the skyline length and visible landmark surface area is evaluated against ground observations. The obtained results show that V-Pan can evaluate landmark visibility with an accuracy of approximately 75%. The key contributions of the work to visibility analysis of urban landmarks are in the inverse viewshed strategy and evaluation of the visual exposure parameters on LiDAR virtual panoramas. Numéro de notice : A2022-206 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2021.2015600 Date de publication en ligne : 17/12/2021 En ligne : https://doi.org/10.1080/13658816.2021.2015600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100021
in International journal of geographical information science IJGIS > vol 36 n° 3 (March 2022) . - pp 476 - 495[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2022031 SL Revue Centre de documentation Revues en salle Disponible Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) / Langning Huo in Remote sensing of environment, vol 270 (March 2022)
[article]
Titre : Towards low vegetation identification: A new method for tree crown segmentation from LiDAR data based on a symmetrical structure detection algorithm (SSD) Type de document : Article/Communication Auteurs : Langning Huo, Auteur ; Eva Lindberg, Auteur ; Johan Holmgren, Auteur Année de publication : 2022 Article en page(s) : n° 112857 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] diamètre à hauteur de poitrine
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt boréale
[Termes IGN] hauteur à la base du houppier
[Termes IGN] houppier
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] segmentation
[Termes IGN] semis de points
[Termes IGN] sous-bois
[Termes IGN] sous-étage
[Termes IGN] strate végétale
[Termes IGN] structure d'un peuplement forestier
[Termes IGN] SuèdeRésumé : (auteur) Obtaining low vegetation data is important in order to quantify the structural characteristics of a forest. Dense three-dimensional (3D) laser scanning data can provide information on the vertical profile of a forest. However, most studies have focused on the dominant and subdominant layers of the forest, while few studies have tried to delineate the low vegetation. To address this issue, we propose a framework for individual tree crown (ITC) segmentation from laser data that focuses on both overstory and understory trees. The framework includes 1) a new algorithm (SSD) for 3D ITC segmentation of dominant trees, by detecting the symmetrical structure of the trees, and 2) removing points of dominant trees and mean shift clustering of the low vegetation. The framework was tested on a boreal forest in Sweden and the performance was compared 1) between plots with different stem density levels, vertical complexities, and tree species composition, and 2) using airborne laser scanning (ALS) data, terrestrial laser scanning (TLS) data, and merged ALS and TLS data (ALS + TLS data). The proposed framework achieved detection rates of 0.87 (ALS + TLS), 0.86 (TLS), and 0.76 (ALS) when validated with field-inventory data (of trees with a diameter at breast height ≥ 4 cm). When validating the estimated number of understory trees by visual interpretation, the framework achieved 19%, 21%, and 39% root-mean-square error values with ALS + TLS, TLS, and ALS data, respectively. These results show that the SSD algorithm can successfully separate laser points of overstory and understory trees, ensuring the detection and segmentation of low vegetation in forest. The proposed framework can be used with both ALS and TLS data, and achieve ITC segmentation for forests with various structural attributes. The results also illustrate the potential of using ALS data to delineate low vegetation. Numéro de notice : A2022-127 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.rse.2021.112857 Date de publication en ligne : 03/01/2022 En ligne : https://doi.org/10.1016/j.rse.2021.112857 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99707
in Remote sensing of environment > vol 270 (March 2022) . - n° 112857[article]Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach / Linyuan Li in International journal of applied Earth observation and geoinformation, vol 107 (March 2022)
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Titre : Ultrahigh-resolution boreal forest canopy mapping: Combining UAV imagery and photogrammetric point clouds in a deep-learning-based approach Type de document : Article/Communication Auteurs : Linyuan Li, Auteur ; Xihan Mu, Auteur ; Francesco Chianucci, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 102686 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] algorithme SLIC
[Termes IGN] apprentissage profond
[Termes IGN] canopée
[Termes IGN] carte forestière
[Termes IGN] Chine
[Termes IGN] classification par maximum de vraisemblance
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] couvert forestier
[Termes IGN] données d'entrainement (apprentissage automatique)
[Termes IGN] données lidar
[Termes IGN] faisceau laser
[Termes IGN] forêt boréale
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de surface de la canopée
[Termes IGN] modèle numérique de terrain
[Termes IGN] segmentation sémantique
[Termes IGN] semis de points
[Termes IGN] sous-étage
[Termes IGN] structure-from-motionRésumé : (auteur) Accurate wall-to-wall estimation of forest crown cover is critical for a wide range of ecological studies. Notwithstanding the increasing use of UAVs in forest canopy mapping, the ultrahigh-resolution UAV imagery requires an appropriate procedure to separate the contribution of understorey from overstorey vegetation, which is complicated by the spectral similarity between the two forest components and the illumination environment. In this study, we investigated the integration of deep learning and the combined data of imagery and photogrammetric point clouds for boreal forest canopy mapping. The procedure enables the automatic creation of training sets of tree crown (overstorey) and background (understorey) data via the combination of UAV images and their associated photogrammetric point clouds and expands the applicability of deep learning models with self-supervision. Based on the UAV images with different overlap levels of 12 conifer forest plots that are categorized into “I”, “II” and “III” complexity levels according to illumination environment, we compared the self-supervised deep learning-predicted canopy maps from original images with manual delineation data and found an average intersection of union (IoU) larger than 0.9 for “complexity I” and “complexity II” plots and larger than 0.75 for “complexity III” plots. The proposed method was then compared with three classical image segmentation methods (i.e., maximum likelihood, Kmeans, and Otsu) in the plot-level crown cover estimation, showing outperformance in overstorey canopy extraction against other methods. The proposed method was also validated against wall-to-wall and pointwise crown cover estimates using UAV LiDAR and in situ digital cover photography (DCP) benchmarking methods. The results showed that the model-predicted crown cover was in line with the UAV LiDAR method (RMSE of 0.06) and deviate from the DCP method (RMSE of 0.18). We subsequently compared the new method and the commonly used UAV structure-from-motion (SfM) method at varying forward and lateral overlaps over all plots and a rugged terrain region, yielding results showing that the method-predicted crown cover was relatively insensitive to varying overlap (largest bias of less than 0.15), whereas the UAV SfM-estimated crown cover was seriously affected by overlap and decreased with decreasing overlap. In addition, canopy mapping over rugged terrain verified the merits of the new method, with no need for a detailed digital terrain model (DTM). The new method is recommended to be used in various image overlaps, illuminations, and terrains due to its robustness and high accuracy. This study offers opportunities to promote forest ecological applications (e.g., leaf area index estimation) and sustainable management (e.g., deforestation). Numéro de notice : A2022-192 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102686 Date de publication en ligne : 05/02/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102686 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99951
in International journal of applied Earth observation and geoinformation > vol 107 (March 2022) . - n° 102686[article]Comparing methods to extract crop height and estimate crop coefficient from UAV imagery using structure from motion / Nitzan Malachy in Remote sensing, vol 14 n° 4 (February-2 2022)PermalinkIntegrating terrestrial laser scanning and unmanned aerial vehicle photogrammetry to estimate individual tree attributes in managed coniferous forests in Japan / Katsuto Shimizu in International journal of applied Earth observation and geoinformation, vol 106 (February 2022)PermalinkPCEDNet: a lightweight neural network for fast and interactive edge detection in 3D point clouds / Chems-Eddine Himeur in ACM Transactions on Graphics, TOG, Vol 41 n° 1 (February 2022)PermalinkPlanning of commercial thinnings using machine learning and airborne Lidar data / Tauri Arumäe in Forests, vol 13 n° 2 (February 2022)PermalinkQuantifying the shape of urban street trees and evaluating its influence on their aesthetic functions based on mobile lidar data / Tianyu Hu in ISPRS Journal of photogrammetry and remote sensing, vol 184 (February 2022)PermalinkRecurrent origin–destination network for exploration of human periodic collective dynamics / Xiaojian Chen in Transactions in GIS, vol 26 n° 1 (February 2022)PermalinkThree-Dimensional point cloud analysis for building seismic damage information / Fan Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 2 (February 2022)Permalink3D modeling of urban area based on oblique UAS images - An end-to-end pipeline / Valeria-Ersilia Oniga in Remote sensing, vol 14 n° 2 (January-2 2022)PermalinkPermalink3D stem modelling in tropical forest: towards improved biomass and biomass change estimates / Sébastien Bauwens (2022)Permalink