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scientifique

How to optimize the 2D/3D urban thermal environment: Insights derived from UAV LiDAR/multispectral data and multi-source remote sensing data / Rongfang Lyu in Sustainable Cities and Society, vol 88 (January 2023)  

Public [article]  inSustainable Cities and Society > vol 88 (January 2023) . - n° 104287 Titre : How to optimize the 2D/3D urban thermal environment: Insights derived from UAV LiDAR/multispectral data and multi-source remote sensing data Type de document : Article/Communication Auteurs : Rongfang Lyu, Auteur ; Jili Pang, Auteur ; Xiaolei Tian, Auteur ; et al., Auteur Année de publication : 2023 Article en page(s) : n° 104287 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] Chine [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] espace vert [Termes IGN] hauteur du bâti [Termes IGN] ilot thermique urbain [Termes IGN] image captée par drone [Termes IGN] image Landsat-OLI [Termes IGN] image multibande [Termes IGN] image Sentinel-MSI [Termes IGN] Leaf Area Index [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] optimisation (mathématiques) [Termes IGN] paysage urbain [Termes IGN] plan d'eau [Termes IGN] planification urbaine [Termes IGN] réseau bayesien [Termes IGN] semis de points [Termes IGN] température au sol Résumé : (auteur) The systematical exploration of how two-dimensional (2D) and three-dimensional (3D) features of urban landscapes influence land surface temperature (LST) is still limited. Therefore, we investigated the influence of three main urban landscapes—urban green space, impervious land, and water bodies on LST, with a particular focus on the 3D vegetation metrics of green volume (GV) and leaf area index (LAI). We used Yinchuan City, China, as a case study. We quantified the impacts of various 2D/3D metrics of the three landscape types on LST using a random forest analysis with multiple sources, including Unmanned Aerial Vehicle (UAV) and remote sensing images. We then generated a Bayesian Network (BN) model to identify the optimal configurations for each landscape type. We found that using 11 of the 31 metrics considered, our model could explain 81.8% of the observed variance in LST of Yinchuan City. Among those, water body metrics were the most important, followed by vegetation abundance, impervious land metrics, and landscape pattern of urban green space. The mean classification error of the BN model was only 22.9%. We suggest that this makes the BN model a promising support tool for urban planning with a view to urban heat island mitigation. Our findings also stress the importance of considering both 2D and 3D features when considering urban cooling strategies. Numéro de notice : A2023-007 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.104287 Date de publication en ligne : 02/11/2022 En ligne : https://doi.org/10.1016/j.scs.2022.104287 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102095 [article]

Urban infrastructure expansion and artificial light pollution degrade coastal ecosystems, increasing natural-to-urban structural connectivity / Moisés A. Aguilera in Landscape and Urban Planning, vol 229 (January 2023)  

Public [article]  inLandscape and Urban Planning > vol 229 (January 2023) . - n° 104609 Titre : Urban infrastructure expansion and artificial light pollution degrade coastal ecosystems, increasing natural-to-urban structural connectivity Type de document : Article/Communication Auteurs : Moisés A. Aguilera, Auteur ; Maria Gracia González, Auteur Année de publication : 2023 Article en page(s) : n° 104609 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] ArcGIS [Termes IGN] Chili [Termes IGN] croissance urbaine [Termes IGN] dégradation de l'environnement [Termes IGN] écosystème [Termes IGN] étalement urbain [Termes IGN] habitat (nature) [Termes IGN] intensité lumineuse [Termes IGN] littoral [Termes IGN] méthode de Monte-Carlo [Termes IGN] paysage urbain [Termes IGN] pollution lumineuse [Termes IGN] urbanisme Résumé : (auteur) Urbanization is provoking habitat loss and fragmentation, driving rapid landscape transformation worldwide. Remnant habitats in urban areas can be especially prone to degradation by human activities at short time scales, and poor planning during urban expansion can erode their structural and functional connectivity. Foredunes in particular are threatened significantly by human activities, including coastal urban infrastructure expansion, by bulldozing them and/or by interrupting their continuity across the shoreline, and also by associated light pollution. However, there is still scarce quantification about how urban processes determine changes in remnant habitat extent and modify the configuration of structural connectivity in coastal urban settings. Using an expanding conurbation located in north-central Chile (∼29°S) as model system, we investigated the rate of coastal foredune loss and spatial fragmentation due to urban expansion, and the change in the type of structural connectivity, i.e. with other natural habitats vs with urban infrastructure. Based on map analyses of structural connectivity among habitats and with urban infrastructure through time, we estimated foredune habitat extent and fragmentation and their shared border with other habitats and built infrastructure during two time intervals, 2010–2015 and 2015–2020. Distribution and intensity of light pollution on present foredunes were also quantified in situ through field sampling. We found 36 % decline in foredune area and increase in their connection with urban infrastructure. Urban wetlands and parallel dunes also experienced persistent area loss and increase in connection with urban infrastructure. Light pollution was intense in the foredune-beach ecotone. Given the rapid erosion of functional and structural connectivity of natural habitats, it becomes imperious to halt the reduction of remnant habitats and ecotones, and improve natural corridors in urban settings. Numéro de notice : A2023-127 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.landurbplan.2022.104609 Date de publication en ligne : 17/10/2022 En ligne : https://doi.org/10.1016/j.landurbplan.2022.104609 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102507 [article]

GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions / Fatemeh Kazemi in Land use policy, vol 123 (December 2022)  

Public [article]  inLand use policy > vol 123 (December 2022) . - n° 106426 Titre : GIS-based land-use suitability analysis for urban agriculture development based on pollution distributions Type de document : Article/Communication Auteurs : Fatemeh Kazemi, Auteur ; Nazanin Hosseinpour, Auteur Année de publication : 2022 Article en page(s) : n° 106426 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] agriculture [Termes IGN] distribution spatiale [Termes IGN] espace vert [Termes IGN] Iran [Termes IGN] milieu urbain [Termes IGN] paysage urbain [Termes IGN] pollution atmosphérique [Termes IGN] pollution des sols [Termes IGN] processus de hiérarchisation analytique [Termes IGN] utilisation du sol Résumé : (auteur) With recent increases in urban population and development, agricultural lands have been changed to residential areas and industrial settlements. Such urban population growth increases necessitate emerging relatively new strategies and forms in urban parks and landscape designs to meet today's economic, social, and ecological needs toward sustainable development. Urban agriculture is one of the strategies for achieving sustainable development and creating multi-purpose landscapes. Such an approach appears to partially solve the problem of agricultural land reduction and degradation. However, urban pollutants seem to hinder the development of such a sustainable concept in the cities. This research aimed to identify suitable locations for urban agriculture in urban green spaces according to various contamination criteria and the uniform distribution of the green spaces in Mashhad, Iran. In this research, using an Analytical Hierarchy Process (AHP) and a Geographic Information System (GIS) facilitated the decision-making process. It also determined the importance of the land use criteria for urban agricultural development. The results showed that the most suitable areas for urban agricultural development with the least impact of pollutants in Mashhad were the suburbs, especially in the northeast and southeast parts. These research results have practical implications for planning urban agricultural development at the city level across the world. Numéro de notice : A2022-895 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1016/j.landusepol.2022.106426 Date de publication en ligne : 03/11/2022 En ligne : https://doi.org/10.1016/j.landusepol.2022.106426 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102244 [article]

Human perception evaluation system for urban streetscapes based on computer vision algorithms with attention mechanisms / Yunhao Li in Transactions in GIS, vol 26 n° 6 (September 2022)  

Public [article]  inTransactions in GIS > vol 26 n° 6 (September 2022) . - pp 2440 - 2454 Titre : Human perception evaluation system for urban streetscapes based on computer vision algorithms with attention mechanisms Type de document : Article/Communication Auteurs : Yunhao Li, Auteur ; Chunxiao Zhang, Auteur ; Chang Wang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 2440 - 2454 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] attention (apprentissage automatique) [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] détection de cible [Termes IGN] image virtuelle [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] paysage urbain [Termes IGN] segmentation d'image [Termes IGN] vision [Termes IGN] vision par ordinateur Résumé : (auteur) Virtual 3D modeling is widely implemented in urban planning and design. To evaluate urban planning modeling, based on existing computer vision models, this article aims to improve performance in the field of human perception analysis for urban street views. In this study, the PSP module extracts detailed features from recognized objects of different sizes, an attention mechanism is applied to solve the problem of large information differences in pictures, and transfer learning technology is used to expand the model to the field of virtual 3D modeling to extract more representative and universal features, similar to how humans perceive street view information. Finally, we obtain a more objective, stable, and accurate neural network model that imitates human perception. This evaluation model converges within the correct interval on the training and validation datasets compared with an evaluation of virtual modeling by a large number of people. Numéro de notice : A2022-733 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1111/tgis.12882 Date de publication en ligne : 15/12/2021 En ligne : https://doi.org/10.1111/tgis.12882 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101698 [article]

Extracting the urban landscape features of the historic district from street view images based on deep learning: A case study in the Beijing Core area / Siming Yin in ISPRS International journal of geo-information, vol 11 n° 6 (June 2022)  

Public [article]  inISPRS International journal of geo-information > vol 11 n° 6 (June 2022) . - n° 326 Titre : Extracting the urban landscape features of the historic district from street view images based on deep learning: A case study in the Beijing Core area Type de document : Article/Communication Auteurs : Siming Yin, Auteur ; Xian Guo, Auteur ; Jie Jiang, Auteur Année de publication : 2022 Article en page(s) : n° 326 Note générale : résumé Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] attention (apprentissage automatique) [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] extraction de traits caractéristiques [Termes IGN] image Streetview [Termes IGN] paysage urbain [Termes IGN] Pékin (Chine) [Termes IGN] segmentation sémantique [Termes IGN] site historique Résumé : (auteur) Accurate extraction of urban landscape features in the historic district of China is an essential task for the protection of the cultural and historical heritage. In recent years, deep learning (DL)-based methods have made substantial progress in landscape feature extraction. However, the lack of annotated data and the complex scenarios inside alleyways result in the limited performance of the available DL-based methods when extracting landscape features. To deal with this problem, we built a small yet comprehensive history-core street view (HCSV) dataset and propose a polarized attention-based landscape feature segmentation network (PALESNet) in this article. The polarized self-attention block is employed in PALESNet to discriminate each landscape feature in various situations, whereas the atrous spatial pyramid pooling (ASPP) block is utilized to capture the multi-scale features. As an auxiliary, a transfer learning module was introduced to supplement the knowledge of the network, to overcome the shortage of labeled data and improve its learning capability in the historic districts. Compared to other state-of-the-art methods, our network achieved the highest accuracy in the case study of Beijing Core Area, with an mIoU of 63.7% on the HCSV dataset; and thus could provide sufficient and accurate data for further protection and renewal in Chinese historic districts. Numéro de notice : A2022-410 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi11060326 Date de publication en ligne : 28/05/2022 En ligne : https://doi.org/10.3390/ijgi11060326 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100760 [article]

Procedural urban forestry / Till Niese in ACM Transactions on Graphics, TOG, Vol 41 n° 2 (April 2022)  

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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)  

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Exploring the advantages of the maximum entropy model in calibrating cellular automata for urban growth simulation: a comparative study of four methods / Bin Zhang in GIScience and remote sensing, vol 59 n° 1 (2022)  

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Anthropogenic degradation of dunes within a city: a disappearing feature of the cultural landscape of Toruń (Poland) / Pawel Molewski in Journal of maps, vol 17 n° 4 (October 2021)  

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Urban geomorphology of a historical city straddling the Tanaro River (Alessandria, NW Italy) / Andrea Mandarino in Journal of maps, vol 17 n° 4 (October 2021)  

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Fast unsupervised multi-scale characterization of urban landscapes based on Earth observation data / Claire Teillet in Remote sensing, vol 13 n° 12 (June-2 2021)  

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Learning from the informality. Using GIS tools to analyze the structure of autopoietic urban systems in the “smart perspective” / Valerio Di pinto in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)  

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A skyline-based approach for mobile augmented reality / Mehdi Ayadi in The Visual Computer, vol 37 n° 4 (April 2021)  

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Urban expansion in the megacity since 1970s: a case study in Mumbai / Sisi Yu in Geocarto international, vol 36 n° 6 ([01/04/2021])  

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Mapping urban spaces / Lamberto Amistadi (2021)  

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