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Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain / R. Niederheiser in GIScience and remote sensing, vol 58 n° 1 (February 2021)
[article]
Titre : Using automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain Type de document : Article/Communication Auteurs : R. Niederheiser, Auteur ; M. Winkler, Auteur ; V. Di Cecco, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 120 - 137 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie terrestre
[Termes IGN] Alpes
[Termes IGN] caméra numérique
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification semi-dirigée
[Termes IGN] couvert végétal
[Termes IGN] distribution de Poisson
[Termes IGN] données topographiques
[Termes IGN] indice de végétation
[Termes IGN] module linéaire
[Termes IGN] montagne
[Termes IGN] occupation du sol
[Termes IGN] photogrammétrie métrologique
[Termes IGN] semis de pointsRésumé : (auteur) In this paper we present a low-cost approach to mapping vegetation cover by means of high-resolution close-range terrestrial photogrammetry. A total of 249 clusters of nine 1 m2 plots each, arranged in a 3 × 3 grid, were set up on 18 summits in Mediterranean mountain regions and in the Alps to capture images for photogrammetric processing and in-situ vegetation cover estimates. This was done with a hand-held pole-mounted digital single-lens reflex (DSLR) camera. Low-growing vegetation was automatically segmented using high-resolution point clouds. For classifying vegetation we used a two-step semi-supervised Random Forest approach. First, we applied an expert-based rule set using the Excess Green index (ExG) to predefine non-vegetation and vegetation points. Second, we applied a Random Forest classifier to further enhance the classification of vegetation points using selected topographic parameters (elevation, slope, aspect, roughness, potential solar irradiation) and additional vegetation indices (Excess Green Minus Excess Red (ExGR) and the vegetation index VEG). For ground cover estimation the photogrammetric point clouds were meshed using Screened Poisson Reconstruction. The relative influence of the topographic parameters on the vegetation cover was determined with linear mixed-effects models (LMMs). Analysis of the LMMs revealed a high impact of elevation, aspect, solar irradiation, and standard deviation of slope. The presented approach goes beyond vegetation cover values based on conventional orthoimages and in-situ vegetation cover estimates from field surveys in that it is able to differentiate complete 3D surface areas, including overhangs, and can distinguish between vegetation-covered and other surfaces in an automated manner. The results of the Random Forest classification confirmed it as suitable for vegetation classification, but the relative feature importance values indicate that the classifier did not leverage the potential of the included topographic parameters. In contrast, our application of LMMs utilized the topographic parameters and was able to reveal dependencies in the two biomes, such as elevation and aspect, which were able to explain between 87% and 92.5% of variance. Numéro de notice : A2021-258 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1080/15481603.2020.1859264 Date de publication en ligne : 13/01/2021 En ligne : https://doi.org/10.1080/15481603.2020.1859264 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97295
in GIScience and remote sensing > vol 58 n° 1 (February 2021) . - pp 120 - 137[article]Remotely-sensed rip current dynamics and morphological control in high-energy beach environments / Isaac Rodriguez Padilla (2021)
Titre : Remotely-sensed rip current dynamics and morphological control in high-energy beach environments Titre original : Télédétection par système vidéo de la dynamique des courants induits par les vagues et de l’évolution morpholoqique des plages soumises aux houles énergétiques Type de document : Thèse/HDR Auteurs : Isaac Rodriguez Padilla, Auteur ; Bruno Castelle, Directeur de thèse ; Philippe Bonneton, Directeur de thèse Editeur : Bordeaux : Université de Bordeaux 1 Année de publication : 2021 Importance : 156 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse présentée pour obtenir le grade de Docteur de l’Université de Bordeaux, Spécialité : Physique de l'environnementLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] base de données localisées
[Termes IGN] carte bathymétrique
[Termes IGN] courant marin
[Termes IGN] données bathymétriques
[Termes IGN] données topographiques
[Termes IGN] érosion côtière
[Termes IGN] extraction de données
[Termes IGN] géomorphologie locale
[Termes IGN] houle
[Termes IGN] image vidéo
[Termes IGN] océanographie dynamique
[Termes IGN] Pyrénées-atlantiques (64)
[Termes IGN] séquence d'images
[Termes IGN] série temporelle
[Termes IGN] surveillance du littoral
[Termes IGN] tempête
[Termes IGN] trait de côte
[Termes IGN] vagueIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Understanding the surf zone circulation and the morphological changes within the nearshore is essential for both scientific and societal interests. However, direct measurements with in-situ instruments are logistically challenging and expensive. The development of optical remote sensing techniques in combination with low-cost image platforms and open-source algorithms offers the possibility of collecting large amounts of information at a reasonable instrumental and computational cost. This work builds on existing and new video monitoring techniques to remotely sense the nearshore bathymetry as well as the surf zone circulation in a high-energy meso-macro tidal beach environment, including storm events. The methods are validated against a dense data set acquired during an intensive field campaign conducted at Anglet beach, SW France. For the first time the temporal and spatial variability of concurrent nearshore bathymetry and surface currents are addressed under high-energy wave forcing. Note de contenu : 1. Introduction
1.1 General context
1.2 Objectives and approach
1.3 Thesis outline
2. Field site and data
2.1 Study site: La Petite Chambre d’Amour (PCA), Anglet Beach
2.2 October 2018 field experiment
3. Image stabilization
3.1 Preamble
3.2 Introduction
3.3 Article: A Simple and Efficient Image Stabilization Method for Coastal Video Monitoring Video Systems
4. Nearshore bathymetric mapping from video imagery
4.1 Preamble
4.2 Introduction
4.3 Indirect bathymetric mapping
4.4 cBathy algorithm
4.5 cBathy results and previous validation
4.6 cBathy settings for PCA beach field experiment
4.7 Topo-bathymetry surveys comparison
4.8 cBathy results
4.9 cBathy error assessment
4.10 Discussion
4.11 Conclusions
5. Optically derived wave-filtered surface currents
5.1 Preamble
5.2 Introduction
5.3 Article: Wave-Filtered Surf Zone Circulation under High-Energy Waves Derived from Video-Based Optical Systems
5.4 Implications and potential of optically derived wave-filtered surface cur?rents
6. Conclusions and perspectives
6.1 General conclusions
6.2 Research perspectivesNuméro de notice : 26726 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Physique de l'environnement : Bordeaux : 2021 Organisme de stage : Environnements et Paléoenvironnements Océaniques et Continentaux EPOC nature-HAL : Thèse DOI : sans Date de publication en ligne : 19/11/2021 En ligne : https://hal.science/tel-03436157 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99523 Detecting classic Maya settlements with Lidar-derived relief visualizations / Amy E. Thompson in Remote sensing, vol 12 n° 17 (September-1 2020)
[article]
Titre : Detecting classic Maya settlements with Lidar-derived relief visualizations Type de document : Article/Communication Auteurs : Amy E. Thompson, Auteur Année de publication : 2020 Article en page(s) : 29 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] analyse d'image orientée objet
[Termes IGN] Belize
[Termes IGN] données topographiques
[Termes IGN] fouille archéologique
[Termes IGN] modèle numérique de terrain
[Termes IGN] relief
[Termes IGN] semis de points
[Termes IGN] site archéologiqueRésumé : (auteur) In the past decade, Light Detection and Ranging (lidar) has fundamentally changed our ability to remotely detect archaeological features and deepen our understanding of past human-environment interactions, settlement systems, agricultural practices, and monumental constructions. Across archaeological contexts, lidar relief visualization techniques test how local environments impact archaeological prospection. This study used a 132 km2 lidar dataset to assess three relief visualization techniques—sky-view factor (SVF), topographic position index (TPI), and simple local relief model (SLRM)—and object-based image analysis (OBIA) on a slope model for the non-automated visual detection of small hinterland Classic (250–800 CE) Maya settlements near the polities of Uxbenká and Ix Kuku’il in Southern Belize. Pedestrian survey in the study area identified 315 plazuelas across a 35 km2 area; the remaining 90 km2 in the lidar dataset is yet to be surveyed. The previously surveyed plazuelas were compared to the plazuelas visually identified on the TPI and SLRM. In total, an additional 563 new possible plazuelas were visually identified across the lidar dataset, using TPI and SLRM. Larger plazuelas, and especially plazuelas located in disturbed environments, are often more likely to be detected in a visual assessment of the TPI and SLRM. These findings emphasize the extent and density of Classic Maya settlements and highlight the continued need for pedestrian survey to ground-truth remotely identified archaeological features and the impact of modern anthropogenic behaviors for archaeological prospection. Remote sensing and lidar have deepened our understanding of past human settlement systems and low-density urbanism, processes that we experience today as humans residing in modern cities Numéro de notice : A2020-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12172838 Date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.3390/rs12172838 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95944
in Remote sensing > vol 12 n° 17 (September-1 2020) . - 29 p.[article]Recognition of building group patterns using graph convolutional network / Rong Zhao in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)
[article]
Titre : Recognition of building group patterns using graph convolutional network Type de document : Article/Communication Auteurs : Rong Zhao, Auteur ; Tinghua Ai, Auteur ; Wenhao Yu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 400 - 417 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données topographiques
[Termes IGN] espace urbain
[Termes IGN] généralisation du bâti
[Termes IGN] graphe
[Termes IGN] modélisation du bâti
[Termes IGN] reconnaissance de formesRésumé : (auteur) Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network based on graph convolutions to automatically identify building group patterns with arbitrary forms. The method first models buildings by a general graph, and then the neural network simultaneously learns the structural information as well as vertex attributes to classify building objects. We apply this method to real building data, and the experimental results show that the proposed method can effectively capture spatial information to make more accurate predictions than traditional methods. Numéro de notice : A2020-510 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1757512 Date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1080/15230406.2020.1757512 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95663
in Cartography and Geographic Information Science > Vol 47 n° 5 (September 2020) . - pp 400 - 417[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 032-2020051 RAB Revue Centre de documentation En réserve L003 Disponible Methodology of the automatic generalization of buildings, road networks, forests and surface waters: a case study based on the Topographic Objects Database in Poland / Izabela Karsznia in Geocarto international, vol 35 n° 7 ([15/05/2020])
[article]
Titre : Methodology of the automatic generalization of buildings, road networks, forests and surface waters: a case study based on the Topographic Objects Database in Poland Type de document : Article/Communication Auteurs : Izabela Karsznia, Auteur ; Marta Przychodzeń, Auteur ; Karolina Sielicka, Auteur Année de publication : 2020 Article en page(s) : pp 735 - 758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] ArcGIS
[Termes IGN] base de connaissances
[Termes IGN] base de données orientée objet
[Termes IGN] bâtiment
[Termes IGN] données topographiques
[Termes IGN] eau de surface
[Termes IGN] forêt
[Termes IGN] placement automatique des objets
[Termes IGN] Pologne
[Termes IGN] réseau routier
[Vedettes matières IGN] GénéralisationRésumé : (auteur) This research presents the formalization and verification of the methodology for the automatic generalization of buildings, road networks, forests and surface waters from the Topographic Objects Database (BDOT10k) in Poland. The article makes the following contributions. First, the generalization methodology contained in the official documents was acquired and presented in the form of the knowledge base. Second, the possibilities and limitations of the implementation of the knowledge base in ArcGIS were discussed. Third, the suitability of the BDOT10k structure for the purpose of automatic generalization performance was verified. As a result of the conducted generalization tests, it was found that the formalization and implementation of the methodology contained in the official specifications, in the automatic mode are not entirely possible. The generalization results, however, are promising. The presented research is in line with the studies recently conducted not only by Polish but also other European National Mapping Agencies. Numéro de notice : A2020-271 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1533591 Date de publication en ligne : 03/12/2018 En ligne : https://doi.org/10.1080/10106049.2018.1533591 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95055
in Geocarto international > vol 35 n° 7 [15/05/2020] . - pp 735 - 758[article]Recognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation / Xianjin He in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)PermalinkRecent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)PermalinkDe l’image optique "multi-stéréo" à la topographie très haute résolution et la cartographie automatique des failles par apprentissage profond / Lionel Matteo (2020)PermalinkHigh‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)PermalinkQuantification of airborne lidar accuracy in coastal dunes (Fire Island, New York) / William J. Schmelz in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 2 (February 2019)PermalinkMachine learning and geographic information systems for large-scale mapping of renewable energy potential / Dan Assouline (2019)PermalinkPermalinkL’utilisation des données écologiques de l’inventaire pour mieux appréhender les conditions locales de milieu (atelier de travail) [diaporama] / Philippe Dreyfus (2018)PermalinkProduction de données topographiques de référence de l'Eurométropole de Strasbourg / Olivier Banaszak in XYZ, n° 153 (décembre 2017 - février 2018)PermalinkPredicting palustrine wetland probability using random forest machine learning and digital elevation data-derived terrain variables / Aaron E. Maxwell in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 6 (June 2016)Permalink