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Termes IGN > aménagement > urbanisme
urbanisme
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Aménagement urbain, Développement urbain, Habitat (urbanisme), Planification urbaine, Ville modèle. Synonyme(s)aménagement urbainVoir aussi |
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Titre : Learnable Earth Parser: Discovering 3D Prototypes in Aerial Scans Type de document : Article/Communication Auteurs : Romain Loiseau , Auteur ; Elliot Vincent, Auteur ; Mathieu Aubry, Auteur ; Loïc Landrieu , Auteur Editeur : Ithaca [New York - Etats-Unis] : ArXiv - Université Cornell Année de publication : 2023 Importance : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] information complexe
[Termes IGN] scène 3D
[Termes IGN] semis de points
[Termes IGN] zone urbaineRésumé : (auteur) We propose an unsupervised method for parsing large 3D scans of real-world scenes into interpretable parts. Our goal is to provide a practical tool for analyzing 3D scenes with unique characteristics in the context of aerial surveying and mapping, without relying on application-specific user annotations. Our approach is based on a probabilistic reconstruction model that decomposes an input 3D point cloud into a small set of learned prototypical shapes. Our model provides an interpretable reconstruction of complex scenes and leads to relevant instance and semantic segmentations. To demonstrate the usefulness of our results, we introduce a novel dataset of seven diverse aerial LiDAR scans. We show that our method outperforms state-of-the-art unsupervised methods in terms of decomposition accuracy while remaining visually interpretable. Our method offers significant advantage over existing approaches, as it does not require any manual annotations, making it a practical and efficient tool for 3D scene analysis. Our code and dataset are available at https://imagine.enpc.fr/~loiseaur/learnable-earth-parser Numéro de notice : P2023-005 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Preprint nature-HAL : Préprint DOI : sans En ligne : https://hal.science/hal-04135416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=103347 Measuring metro accessibility: An exploratory study of Wuhan based on multi-source urban data / Tao Wu in ISPRS International journal of geo-information, vol 12 n° 1 (January 2023)
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Titre : Measuring metro accessibility: An exploratory study of Wuhan based on multi-source urban data Type de document : Article/Communication Auteurs : Tao Wu, Auteur ; Mingjing Li, Auteur ; Ye Zhou, Auteur Année de publication : 2023 Article en page(s) : n° 18 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] accessibilité
[Termes IGN] analyse de groupement
[Termes IGN] classification par nuées dynamiques
[Termes IGN] données multisources
[Termes IGN] OpenStreetMap
[Termes IGN] planification urbaine
[Termes IGN] point d'intérêt
[Termes IGN] processus de hiérarchisation analytique
[Termes IGN] transport public
[Termes IGN] utilisation du sol
[Termes IGN] Wuhan (Chine)Résumé : (auteur) Metro accessibility has attracted interest in sustainable transport analyses. Hence, the accuracy of metro-accessibility measures have become increasingly vital. Various spatiotemporal factors, including by-metro accessibility, land-use accessibility and to-metro accessibility, affect metro accessibility; however, measuring metro accessibility while considering all these components simultaneously is challenging. By integrating these factors into a unified analysis framework, this study aims to strengthen the method for metro-accessibility assessment. Specifically, we proposed the “By metro–Land use–To metro” model to conduct a metro-accessibility index and develop an accessibility-based station typology. The results show that Wuhan metro system accessibility presented a “high-medium-low” spatial disparity from the urban center to the periphery. Meanwhile, the variety of metro-accessibility characteristics and typologies in Wuhan will equip urban planners and policymakers with a useful tool for better organising by-metro accessibility, land-use accessibility and to-metro accessibility. Numéro de notice : A2023-104 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi12010018 Date de publication en ligne : 10/01/2023 En ligne : https://doi.org/10.3390/ijgi12010018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102432
in ISPRS International journal of geo-information > vol 12 n° 1 (January 2023) . - n° 18[article]A real-time algorithm for continuous navigation in intelligent transportation systems using LiDAR-Gyroscope-Odometer integration / Tarek Hassan in Journal of applied geodesy, vol 17 n° 1 (January 2023)
[article]
Titre : A real-time algorithm for continuous navigation in intelligent transportation systems using LiDAR-Gyroscope-Odometer integration Type de document : Article/Communication Auteurs : Tarek Hassan, Auteur ; Tamer Fath-Allah, Auteur ; Mohamed Elhabiby, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 65 - 77 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] capteur à balayage
[Termes IGN] centrale inertielle
[Termes IGN] gyroscope
[Termes IGN] lidar mobile
[Termes IGN] odomètre
[Termes IGN] panne
[Termes IGN] positionnement par GNSS
[Termes IGN] système de transport intelligent
[Termes IGN] temps réel
[Termes IGN] véhicule automobile
[Termes IGN] zone urbaineRésumé : (auteur) Real-time positioning in suburban and urban environments has been a challenging task for many Intelligent Transportation Systems (ITS) applications. In these environments, positioning using Global Navigation Satellite Systems (GNSS) cannot provide continuous solutions due to the blockage of signals in harsh scenarios. Consequently, it is intrinsic to have an independent positioning system capable of providing accurate and reliable positional solutions over GNSS outages. This study exploits the integration of Light Detection and Ranging (LiDAR), gyroscope, and odometer sensors, and a novel real-time algorithm is proposed for this integration. Real field data, collected by a moving land vehicle, is used to test the presented algorithm. Three simulated GNSS outages are introduced in the trajectory such that each outage lasts for five minutes. The results show that using the proposed algorithm can achieve a promising navigation performance in urban environments. In addition, it is shown that the denser environments, that existed over the second and third outages, can provide better positioning accuracies as more features are extracted. The horizontal errors over the first outage, with less density of surroundings, reached 7.74 m (0.43%) error with a mean value of 3.15 m. Moreover, the horizontal errors in the denser environments over the second and third outages reached 4.97 m (0.28%) and 3.99 m (0.23%), with mean values of 2.25 m and 1.89 m, respectively. Numéro de notice : A2023-110 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1515/jag-2022-0022 Date de publication en ligne : 28/11/2022 En ligne : https://doi.org/10.1515/jag-2022-0022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102469
in Journal of applied geodesy > vol 17 n° 1 (January 2023) . - pp 65 - 77[article]Sensing urban soundscapes from street view imagery / Tianhong Zhao in Computers, Environment and Urban Systems, vol 99 (January 2023)
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Titre : Sensing urban soundscapes from street view imagery Type de document : Article/Communication Auteurs : Tianhong Zhao, Auteur ; Xiucheng Liang, Auteur ; Wei Tu, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 101915 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond
[Termes IGN] bruit (audition)
[Termes IGN] distribution spatiale
[Termes IGN] image Streetview
[Termes IGN] paysage sonore
[Termes IGN] planification urbaine
[Termes IGN] pollution acoustique
[Termes IGN] Shenzhen
[Termes IGN] Singapour
[Termes IGN] ville durable
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) A healthy acoustic environment is an essential component of sustainable cities. Various noise monitoring and simulation techniques have been developed to measure and evaluate urban sounds. However, sensing large areas at a fine resolution remains a great challenge. Based on machine learning, we introduce a new application of street view imagery — estimating large-area high-resolution urban soundscapes, investigating the premise that we can predict and characterize soundscapes without laborious and expensive noise measurements. First, visual features are extracted from street-level imagery using computer vision. Second, fifteen soundscape indicators are identified and a survey is conducted to gauge them solely from images. Finally, a prediction model is constructed to infer the urban soundscape by modeling the non-linear relationship between them. The results are verified with extensive field surveys. Experiments conducted in Singapore and Shenzhen using half a million images affirm that street view imagery enables us to sense large-scale urban soundscapes with low cost but high accuracy and detail, and provides an alternative means to generate soundscape maps. reaches 0.48 by evaluating the predicted results with field data collection. Further novelties in this domain are revealing the contributing visual elements and spatial laws of soundscapes, underscoring the usability of crowdsourced data, and exposing international patterns in perception. Numéro de notice : A2023-014 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article DOI : 10.1016/j.compenvurbsys.2022.101915 Date de publication en ligne : 20/11/2022 En ligne : https://doi.org/10.1016/j.compenvurbsys.2022.101915 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102131
in Computers, Environment and Urban Systems > vol 99 (January 2023) . - n° 101915[article]The cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan / Muhammad Nasar Ahmad in Photogrammetric Engineering & Remote Sensing, PERS, vol 89 n° 1 (January 2023)
[article]
Titre : The cellular automata approach in dynamic modelling of land use change detection and future simulations based on remote sensing data in Lahore Pakistan Type de document : Article/Communication Auteurs : Muhammad Nasar Ahmad, Auteur ; Zhenfeng Shao, Auteur ; Akib Javed, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : pp 47 - 55 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] automate cellulaire
[Termes IGN] carte thématique
[Termes IGN] classification semi-dirigée
[Termes IGN] détection de changement
[Termes IGN] données vectorielles
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] MNS SRTM
[Termes IGN] modèle dynamique
[Termes IGN] occupation du sol
[Termes IGN] Pakistan
[Termes IGN] surveillance de l'urbanisation
[Termes IGN] utilisation du solRésumé : (auteur) Rapid urbanization has become an immense problem in Lahore city, causing various socio-economic and environmental problems. Therefore, it is noteworthy to monitor land use/land cover (LULC) change detection and future LULC patterns in Lahore. The present study focuses on evaluating the current extent and modeling the future LULC developments in Lahore, Pakistan. Therefore, the semi-automatic classification model has been applied for the classification of Landsat satellite imagery from 2000 to 2020. And the Modules of Land Use Change Evaluation (MOLUSCE) cellular automata (CA-ANN) model was implemented to simulate future land use trends for the years 2030 and 2040. This study project made use of Landsat, Shuttle Radar Topography Mission Digital Elevation Model, and vector data. The research methodology includes three main steps: (i) semi-automatic land use classification using Landsat data from 2000 to 2020; (ii) future land use prediction using the CA-ANN (MOLUSCE) model; and (iii) monitoring change detection and interpretation of results. The research findings indicated that there was a rise in urban areas and a decline in vegetation, barren land, and water bodies for both the past and future projections. The results also revealed that about 27.41% of the urban area has been increased from 2000 to 2020 with a decrease of 42.13% in vegetation, 2.3% in barren land, and 6.51% in water bodies, respectively. The urban area is also expected to grow by 23.15% between 2020 and 2040, whereas vegetation, barren land, and water bodies will all decline by 28.05%, 1.8%, and 12.31%, respectively. Results can also aid in the long-term, sustainable planning of the city. It was also observed that the majority of the city's urban area expansion was found to have occurred in the city's eastern and southern regions. This research also suggests that decision-makers and municipal Government should reconsider city expansion strategies. Moreover, the future city master plans of 2050 must emphasize the relevance of rooftop urban planting and natural resource conservation. Numéro de notice : A2023-047 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : https://doi.org/10.14358/PERS.22-00102R2 Date de publication en ligne : 01/01/2023 En ligne : https://doi.org/10.14358/PERS.22-00102R2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102357
in Photogrammetric Engineering & Remote Sensing, PERS > vol 89 n° 1 (January 2023) . - pp 47 - 55[article]Réservation
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