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Developing a data-fusing method for mapping fine-scale urban three-dimensional building structure / Xinxin Wu in Sustainable Cities and Society, vol 80 (May 2022)  

Public [article]  inSustainable Cities and Society > vol 80 (May 2022) . - n° 103716 Titre : Developing a data-fusing method for mapping fine-scale urban three-dimensional building structure Type de document : Article/Communication Auteurs : Xinxin Wu, Auteur ; Jinpei Ou, Auteur ; Youyue Wen, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : n° 103716 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] apprentissage automatique [Termes IGN] cartographie urbaine [Termes IGN] données localisées 3D [Termes IGN] données multisources [Termes IGN] fusion de données [Termes IGN] hauteur du bâti [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] modèle de régression [Termes IGN] morphologie urbaine [Termes IGN] Shenzhen [Termes IGN] ville durable [Termes IGN] ville intelligente Résumé : (auteur) Understanding urban morphology is essential for various urban management studies and local environmental issues and guiding sustainable city development. Existing studies mainly focus on analyzing urban morphology from the horizontal aspect, while the urban vertical structure has rarely been discussed due to the scarcity of reliable and fine-scale urban three-dimensional (3-D) building data. This study develops an effective data-fusing methodology to estimate the heights of individual buildings at a city scale. We examined a machine-learning regression model by collecting public materials, including multi-source remote sensing-(RS)-based products, building-derived features, and relevant data to verify its performance in building height estimation. By applying the model in Shenzhen City, a dense city in the Guangdong-Hong Kong-Macao Greater Bay Area, results demonstrated that integrating rich multi-source explanatory variables could achieve high-accuracy building height retrieval. Using multiple building morphological metrics derived by building height data as proxy measures, the urban 3-D form patterns were further analyzed to understand current heterogeneous urban morphological structures. The proposed methodology can be conveniently applied to worldwide cities for urban 3-D morphology retrieval. Also, the available building height information is useful for planners to design morphological control for cities and thus contributes to sustainable and smart city development. Numéro de notice : A2022-268 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article DOI : 10.1016/j.scs.2022.103716 Date de publication en ligne : 12/02/2022 En ligne : https://doi.org/10.1016/j.scs.2022.103716 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100279 [article]

Improving urban land cover mapping with the fusion of optical and SAR data based on feature selection strategy / Qing Ding in Photogrammetric Engineering & Remote Sensing, PERS, vol 88 n° 1 (January 2022)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 88 n° 1 (January 2022) . - pp 17 - 28 Titre : Improving urban land cover mapping with the fusion of optical and SAR data based on feature selection strategy Type de document : Article/Communication Auteurs : Qing Ding, Auteur ; Zhenfeng Shao, Auteur ; Xiao Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 17 - 28 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] analyse comparative [Termes IGN] carte d'occupation du sol [Termes IGN] cartographie urbaine [Termes IGN] Chine [Termes IGN] fusion de données multisource [Termes IGN] image optique [Termes IGN] image radar [Termes IGN] précision de la classification Résumé : (Auteur) Taking the Futian District as the research area, this study proposed an effective urban land cover mapping framework fusing optical and SAR data. To simplify the model complexity and improve the mapping results, various feature selection methods were compared and evaluated. The results showed that feature selection can eliminate irrelevant features, increase the mean correlation between features slightly, and improve the classification accuracy and computational efficiency significantly. The recursive feature elimination-support vector machine (RFE-SVM) model obtained the best results, with an overall accuracy of 89.17% and a kappa coefficient of 0.8695, respectively. In addition, this study proved that the fusion of optical and SAR data can effectively improve mapping and reduce the confusion between different land covers. The novelty of this study is with the insight into the merits of multi-source data fusion and feature selection in the land cover mapping process over complex urban environments, and to evaluate the performance differences between different feature selection methods. Numéro de notice : A2022-061 Affiliation des auteurs : non IGN Thématique : URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.21-00030R2 Date de publication en ligne : 01/01/2022 En ligne : https://doi.org/10.14358/PERS.21-00030R2 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99703 [article]

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Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images / Xiao Li in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)  

Public [article]  inCartography and Geographic Information Science > vol 49 n° 1 (January 2022) . - pp 32 - 49 Titre : Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images Type de document : Article/Communication Auteurs : Xiao Li, Auteur ; Huan Ning, Auteur ; Xiao Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 32 - 49 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] carrefour [Termes IGN] cartographie urbaine [Termes IGN] couche thématique [Termes IGN] exploration d'images [Termes IGN] feu de circulation [Termes IGN] image Streetview [Termes IGN] Mapillary [Termes IGN] réseau routier [Termes IGN] segmentation d'image [Termes IGN] signalisation routière Résumé : (auteur) Auditing and mapping traffic infrastructure is a crucial task in urban management. For example, signalized intersections play an essential role in transportation management; however, effectively identifying these intersections remains unsolved. Traditionally, signalized intersection data are manually collected through field audits or checking street view images (SVIs), which is time-consuming and labor-intensive. This study proposes an effective protocol to identify signalized intersections using road networks and SVIs. First, we propose a six-step geoprocessing model to generate an intersection feature layer from road networks. Second, we utilize up to three nearest SVIs to capture streetscapes at each intersection. Then, a deep learning-based image segmentation model is adopted to recognize traffic light-related pixels from each SVI. Last, we design a post-processing step to generate new features characterizing SVIs’ segmentation results at each intersection and build a decision tree model to determine the traffic control type. Results demonstrate that the proposed protocol can effectively identify signalized intersections with an overall accuracy of 97.05%. It also proves the effectiveness of SVIs for auditing urban infrastructures. This study can directly benefit transportation agencies by providing a ready-to-use smart audit and mapping solution for large-scale identification and mapping of signalized intersections. Numéro de notice : A2022-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1080/15230406.2021.1992299 Date de publication en ligne : 16/11/2021 En ligne : https://doi.org/10.1080/15230406.2021.1992299 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99148 [article]

The accuracy of urban maps in Spain through GIS: The example of Burgos from the nineteenth to the twentieth century / Barbara Polo-Martin in Cartographica, vol 56 n° 3 (Fall 2021)  

Public [article]  inCartographica > vol 56 n° 3 (Fall 2021) . - pp 236 - 250 Titre : The accuracy of urban maps in Spain through GIS: The example of Burgos from the nineteenth to the twentieth century Type de document : Article/Communication Auteurs : Barbara Polo-Martin, Auteur Année de publication : 2021 Article en page(s) : pp 236 - 250 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] analyse diachronique [Termes IGN] cartographie ancienne [Termes IGN] cartographie cadastrale [Termes IGN] cartographie urbaine [Termes IGN] Castille-et-Leon (Espagne) [Termes IGN] croissance urbaine [Termes IGN] dix-neuvième siècle [Termes IGN] superposition de données [Termes IGN] système d'information géographique [Termes IGN] vingtième siècle Résumé : (auteur) Burgos, in Spain, due to its geographical and historical importance, which made it a politically, militarily, and administratively key city in the configuration of Spain throughout the history of the country, has a large amount of cartographic documentation. Therefore, it has been necessary to carry out different phases of work to collect and analyze the cartographic material available, as well as to specify the maps and plans that would be used to convey and structure the cartography of Burgos during the nineteenth and twentieth centuries. However, we must take into account in any study that, despite advances in technology, including machines used to digitize these artifacts, there remains a degree of error, so the display of the map that the researcher observes is not as reliable as it should be. Taking into account the hypothetical character of the accuracy of the maps collected and used in this study, and in order to achieve its goals, a thematic analysis through selection, geolocation, and comparison with the current city map based on different criteria is proposed. Thanks to the rich material, this case can be extrapolated to other cities in the country and the process of making up a map during the nineteenth and twentieth centuries can be known in a deeper way. Numéro de notice : A2021-706 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3138/cart-2020-0008 Date de publication en ligne : 30/09/2021 En ligne : https://doi.org/10.3138/cart-2020-0008 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98596 [article]

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Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping / Jiadi Yin in Remote sensing, vol 13 n° 8 (April-2 2021)  

Public [article]  inRemote sensing > vol 13 n° 8 (April-2 2021) . - n° 1579 Titre : Decision-level and feature-level integration of remote sensing and geospatial big data for urban land use mapping Type de document : Article/Communication Auteurs : Jiadi Yin, Auteur ; Ping Fu, Auteur ; Nicholas A.S. Hamm, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 1579 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] carte d'utilisation du sol [Termes IGN] cartographie urbaine [Termes IGN] Chine [Termes IGN] données massives [Termes IGN] image Sentinel-MSI [Termes IGN] intégration de données [Termes IGN] OpenStreetMap [Termes IGN] point d'intérêt [Termes IGN] zone urbaine Résumé : (auteur) Information about urban land use is important for urban planning and sustainable development. The emergence of geospatial big data (GBD), increased the availability of remotely sensed (RS) data and the development of new methods for data integration to provide new opportunities for mapping types of urban land use. However, the modes of RS and GBD integration are diverse due to the differences in data, study areas, classifiers, etc. In this context, this study aims to summarize the main methods of data integration and evaluate them via a case study of urban land use mapping in Hangzhou, China. We first categorized the RS and GBD integration methods into decision-level integration (DI) and feature-level integration (FI) and analyzed their main differences by reviewing the existing literature. The two methods were then applied for mapping urban land use types in Hangzhou city, based on urban parcels derived from the OpenStreetMap (OSM) road network, 10 m Sentinel-2A images, and points of interest (POI). The corresponding classification results were validated quantitatively and qualitatively using the same testing dataset. Finally, we illustrated the advantages and disadvantages of both approaches via bibliographic evidence and quantitative analysis. The results showed that: (1) The visual comparison indicates a generally better performance of DI-based classification than FI-based classification; (2) DI-based urban land use mapping is easy to implement, while FI-based land use mapping enables the mixture of features; (3) DI-based and FI-based methods can be used together to improve urban land use mapping, as they have different performances when classifying different types of land use. This study provides an improved understanding of urban land use mapping in terms of the RS and GBD integration strategy. Numéro de notice : A2021-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13081579 Date de publication en ligne : 19/04/2021 En ligne : https://doi.org/10.3390/rs13081579 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97634 [article]

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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Characterizing urban land changes of 30 global megacities using nighttime light time series stacks / Qiming Zheng in ISPRS Journal of photogrammetry and remote sensing, vol 173 (March 2021)  

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Unmixing-based Sentinel-2 downscaling for urban land cover mapping / Fei Xu in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)  

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Worldwide detection of informal settlements via topological analysis of crowdsourced digital maps / Satej Soman in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

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Local color and morphological image feature based vegetation identification and its application to human environment street view vegetation mapping, or how green is our county? / Istvan G. Lauko in Geo-spatial Information Science, vol 23 n° 3 (September 2020)  

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Extraction of urban built-up areas from nighttime lights using artificial neural network / Tingting Xu in Geocarto international, vol 35 n° 10 ([01/08/2020])  

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Triangulation network of 1929–1944 of the first 1:500 urban map of València / Miriam Villar-Cano in Survey review, vol 52 n° 373 (July 2020)  

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Estimating and interpreting fine-scale gridded population using random forest regression and multisource data / Yun Zhou in ISPRS International journal of geo-information, vol 9 n° 6 (June 2020)  

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Mapping urban grey and green structures for liveable cities using a 3D enhanced OBIA approach and vital statistics / E. Banzhaf in Geocarto international, vol 35 n° 6 ([01/05/2020])  

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Heuristic sample learning for complex urban scenes: Application to urban functional-zone mapping with VHR images and POI data / Xiuyuan Zhang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)  

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