Centre dedocumentation
scientifique

Extracting urban landmarks from geographical datasets using a random forests classifier / Yue Lin in International journal of geographical information science IJGIS, vol 33 n°12 (December 2019)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 33 n°12 (December 2019) . - pp 2406 - 2423 Titre : Extracting urban landmarks from geographical datasets using a random forests classifier Type de document : Article/Communication Auteurs : Yue Lin, Auteur ; Yuyang Cai, Auteur ; Yue Gong, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 2406 - 2423 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] classification par forêts aléatoires [Termes descripteurs IGN] extraction automatique [Termes descripteurs IGN] gestion des itinéraires [Termes descripteurs IGN] jeu de données localisées [Termes descripteurs IGN] point de repère [Termes descripteurs IGN] précision de la classification [Termes descripteurs IGN] représentation mentale spatiale [Termes descripteurs IGN] saillance [Termes descripteurs IGN] Shenzhen [Termes descripteurs IGN] ville Résumé : (auteur) Urban landmarks are of significant importance to spatial cognition and route navigation. However, the current landmark extraction methods mainly focus on the visual salience of landmarks and are insufficient for obtaining high extraction accuracy when the size of the geographical dataset varies. This study introduces a random forests (RF) classifier combining with the synthetic minority oversampling technique (SMOTE) in urban landmark extraction. Both GIS and social sensing data are employed to quantify the structural and cognitive salience of the examined urban features, which are available from basic spatial databases or mainstream web service application programming interfaces (APIs). The results show that the SMOTE-RF model performs well in urban landmark extraction, with the values of recall, precision, F-measure and AUC reaching 0.851, 0.831, 0.841 and 0.841, respectively. Additionally, this method is suitable for both large and small geographical datasets. The ranking of variable importance given by this model further indicates that certain cognitive measures – such as feature class, Weibo popularity and Bing popularity – can serve as crucial factors for determining a landmark. The optimal variable combination for landmark extraction is also acquired, which might provide support for eliminating the variable selection requirement in other landmark extraction methods. Numéro de notice : A2019-426 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2019.1620238 date de publication en ligne : 28/05/2019 En ligne : https://doi.org/10.1080/13658816.2019.1620238 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93559 [article]

Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne / Marcello Marini in Computers, Environment and Urban Systems, vol 78 (November 2019)  

Public [article]  inComputers, Environment and Urban Systems > vol 78 (November 2019) Titre : Immigration and future housing needs in Switzerland: Agent-based modelling of agglomeration Lausanne Type de document : Article/Communication Auteurs : Marcello Marini, Auteur ; Ndaona Chokani, Auteur ; Reza S. Abhari, Auteur Année de publication : 2019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] agglomération [Termes descripteurs IGN] banlieue [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] données spatiotemporelles [Termes descripteurs IGN] immigration [Termes descripteurs IGN] Lausanne [Termes descripteurs IGN] logement [Termes descripteurs IGN] mobilité urbaine [Termes descripteurs IGN] modèle numérique du bâti [Termes descripteurs IGN] modèle orienté agent [Termes descripteurs IGN] périphérie urbaine [Termes descripteurs IGN] projection perspective [Termes descripteurs IGN] système multi-agents Résumé : (auteur) Immigration accounts for 80% of Switzerland's annual population growth, and therefore profoundly impacts demographics, and the attendant housing needs. As there are different possible future scenarios of immigration that will impact urban transformation in Switzerland, we have developed an agent-based dwellings model that, with reasonable computing time due to the use of the computer architecture of graphical processor units, can simulate for a time horizon of decades, the annual evolution of millions of individually characterised households. This dwellings model is coupled to an agent-based population model that simulates millions of individual population agents. We simulate different immigration scenarios, up to 2035, in the Swiss agglomeration of Lausanne. It is shown that the building capacity of the city of Lausanne will reach a limit in 2022, subsequently leading to more rapid growth in the periphery of the agglomeration Lausanne. The construction of new residential dwellings consists primarily of smaller apartments that are more attractive to the demographic of smaller households; this demographic tends to move to the periphery. As families tend to move towards the city centre due to the availability of services, the city and periphery show opposite evolutions over time in the numbers of family households compared to numbers of singles and couples households. The periphery requires an increase in the number and typology of services targeted at the growing demographic of smaller households. Further as most workplaces are still be located in the city centre, the planned improvement of transportation infrastructure in the agglomeration should primarily focus on improved access to the periphery. These observations underline the profound impact of the typology of immigration on the demand for suitable housing, and thus on urban development. Numéro de notice : A2019-413 Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2019.101400 date de publication en ligne : 01/09/2019 En ligne : https://doi.org/10.1016/j.compenvurbsys.2019.101400 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93538 [article]

Pressures and threats to nature related to human activities in European urban and suburban forests / Ewa Referowska-Chodak in Forests, vol 10 n° 9 (September 2019)  

Public [article]  inForests > vol 10 n° 9 (September 2019) . - 26 p. Titre : Pressures and threats to nature related to human activities in European urban and suburban forests Type de document : Article/Communication Auteurs : Ewa Referowska-Chodak, Auteur Année de publication : 2019 Article en page(s) : 26 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] action anthropique [Termes descripteurs IGN] arbre urbain [Termes descripteurs IGN] biomasse forestière [Termes descripteurs IGN] construction [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] écosystème [Termes descripteurs IGN] flore urbaine [Termes descripteurs IGN] gestion forestière [Termes descripteurs IGN] impact sur l'environnement [Termes descripteurs IGN] périphérie urbaine [Termes descripteurs IGN] pollution atmosphérique [Termes descripteurs IGN] urbanisation [Vedettes matières IGN] Ecologie forestière Résumé : (auteur) This review regards the pressures and threats linked with the human use of European urban and suburban forests. They can be divided into the following major categories: urban development, fragmentation, and isolation of forests; human pressures on soil and vegetation (e.g., changes in vegetation due to trampling, environmental and especially air pollution); human pressures on animals (e.g., wildlife losses due to collisions, frequent presence of dogs accompanying the visitors); and other threats and damages (e.g., littering and acts of vandalism). The directions of negative relations between people and forests shown in this review draw attention to the high complexity of the discussed issues. Awareness of this complexity (when planning and implementing forest management) can limit or counteract conflicts arising from the use of urban and suburban forests by people. This is of particular importance in the era of progressing urbanization and the evolution of human needs regarding the use of forests. Numéro de notice : A2019-336 Thématique : FORET/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/f10090765 date de publication en ligne : 04/09/2019 En ligne : https://doi.org/10.3390/f10090765 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93362 [article]

Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network / Chunping Qiu in ISPRS Journal of photogrammetry and remote sensing, vol 154 (August 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 154 (August 2019) . - pp 151 - 162 Titre : Local climate zone-based urban land cover classification from multi-seasonal Sentinel-2 images with a recurrent residual network Type de document : Article/Communication Auteurs : Chunping Qiu, Auteur ; Lichao Mou, Auteur ; Michael Schmitt, Auteur ; Xiao Xiang Zhu, Auteur Année de publication : 2019 Article en page(s) : pp 151 - 162 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] climat urbain [Termes descripteurs IGN] image multitemporelle [Termes descripteurs IGN] image optique [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] occupation du sol [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] réseau neuronal récurrent [Termes descripteurs IGN] résidu [Termes descripteurs IGN] ville Résumé : (Auteur) The local climate zone (LCZ) scheme was originally proposed to provide an interdisciplinary taxonomy for urban heat island (UHI) studies. In recent years, the scheme has also become a starting point for the development of higher-level products, as the LCZ classes can help provide a generalized understanding of urban structures and land uses. LCZ mapping can therefore theoretically aid in fostering a better understanding of spatio-temporal dynamics of cities on a global scale. However, reliable LCZ maps are not yet available globally. As a first step toward automatic LCZ mapping, this work focuses on LCZ-derived land cover classification, using multi-seasonal Sentinel-2 images. We propose a recurrent residual network (Re-ResNet) architecture that is capable of learning a joint spectral-spatial-temporal feature representation within a unitized framework. To this end, a residual convolutional neural network (ResNet) and a recurrent neural network (RNN) are combined into one end-to-end architecture. The ResNet is able to learn rich spectral-spatial feature representations from single-seasonal imagery, while the RNN can effectively analyze temporal dependencies of multi-seasonal imagery. Cross validations were carried out on a diverse dataset covering seven distinct European cities, and a quantitative analysis of the experimental results revealed that the combined use of the multi-temporal information and Re-ResNet results in an improvement of approximately 7 percent points in overall accuracy. The proposed framework has the potential to produce consistent-quality urban land cover and LCZ maps on a large scale, to support scientific progress in fields such as urban geography and urban climatology. Numéro de notice : A2019-268 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.05.004 date de publication en ligne : 14/06/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.05.004 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93085 [article]

Réservation

Réserver ce document

Exemplaires (3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2019081	SL	Revue	Centre de documentation	Revues en salle	Disponible
081-2019083	DEP-RECP	Revue	MATIS	Dépôt en unité	Exclu du prêt
081-2019082	DEP-RECF	Revue	Nancy	Dépôt en unité	Exclu du prêt

CNN-based dense image matching for aerial remote sensing images / Shunping Ji in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 6 (June 2019) . - pp 415 - 424 Titre : CNN-based dense image matching for aerial remote sensing images Type de document : Article/Communication Auteurs : Shunping Ji, Auteur ; Jin Liu, Auteur ; Meng Lu, Auteur Année de publication : 2019 Article en page(s) : pp 415 - 424 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes descripteurs IGN] appariement d'images [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] Chine [Termes descripteurs IGN] couple stéréoscopique [Termes descripteurs IGN] image aérienne [Termes descripteurs IGN] Munich [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] Stuttgart [Termes descripteurs IGN] ville [Termes descripteurs IGN] zone urbaine Résumé : (Auteur) Dense stereo matching plays a key role in 3D reconstruction. The capability of using deep learning in the stereo matching of remote sensing data is currently uncertain. This article investigated the application of deep learning–based stereo methods in aerial image series and proposed a deep learning–based multi-view dense matching framework. First, we applied three typical convolutional neural network models, MC-CNN, GC-Net, and DispNet, to aerial stereo pairs and compared the results with those of the SGM and a commercial software, SURE. Second, on different data sets, the generalization ability of each network is evaluated by using direct transfer learning with models pretrained on other data sets and by fine-tuning with a small number of target training data. Third, we present a deep learning–based multi-view dense matching framework where the multi-view geometry is introduced to further refine matching results. Three sets of aerial images as the main data sets and two open-source sets of street images as auxiliary data sets are used for testing. Experiments show that, first, the performance of deep learning–based stereo methods is slightly better than traditional methods. Second, both the GC-Net and the MC-CNN have demonstrated good generalization ability and can obtain satisfactory results on aerial images using a pretrained model on several available stereo benchmarks. Third, multi-view geometry constraints can further improve the performance of deep learning–based methods, which is better than that of the multi-view–based SGM and SURE. Numéro de notice : A2019-246 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.6.415 date de publication en ligne : 01/06/2019 En ligne : https://doi.org/10.14358/PERS.85.6.415 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93002 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
105-2019061	SL	Revue	Centre de documentation	Revues en salle	Disponible

Multi-scale object detection in remote sensing imagery with convolutional neural networks / Zhipeng Deng in ISPRS Journal of photogrammetry and remote sensing, vol 145 - part A (November 2018)  

Permalink

OpenStreetMap data quality enrichment through awareness raising and collective action tools—experiences from a European project / Amin Mobasheri in Geo-spatial Information Science, vol 21 n° 3 (October 2018)  

Permalink

Spatial discontinuities, health and mobility - What do the Google's POIs and tweets tell us about Bangkok's (Thailand) structures and spatial dynamics? / Alexandre Cebeillac in Revue internationale de géomatique, vol 28 n° 4 (octobre - décembre 2018)  

Permalink

Integrating multi-agent evacuation simulation and multi-criteria evaluation for spatial allocation of urban emergency shelters / Jia Yu in International journal of geographical information science IJGIS, vol 32 n° 9-10 (September - October 2018)  

Permalink

Assessing spatiotemporal predictability of LBSN : a case study of three Foursquare datasets / Ming Li in Geoinformatica [en ligne], vol 22 n° 3 (July 2018)  

Permalink

Evaluation of the cartographical quality of urban plans by eye-tracking / Jaroslav Burian in ISPRS International journal of geo-information, vol 7 n° 5 (May 2018)  

Permalink

Saint-Quentin-en-Yvelines à 2,5 cm / Anonyme in Géomatique expert, n° 121 (mars - avril 2018)

Permalink

The national geographic characteristics of online public opinion propagation in China based on WeChat network / Chuan Ai in Geoinformatica [en ligne], vol 22 n° 2 (April 2018)  

Permalink

3D micro-mapping : Towards assessing the quality of crowdsourcing to support 3D point cloud analysis / Benjamin Herfort in ISPRS Journal of photogrammetry and remote sensing, vol 137 (March 2018)  

Permalink

A new model for cadastral surveying using crowdsourcing / K. Apostolopoulos in Survey review, vol 50 n° 359 (March 2018)  

Permalink