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3D building metrics for urban morphology / Anna Labetski in International journal of geographical information science IJGIS, vol 37 n° 1 (January 2023)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 37 n° 1 (January 2023) Titre : 3D building metrics for urban morphology Type de document : Article/Communication Auteurs : Anna Labetski, Auteur ; Stelios Vitalis, Auteur ; Filip Biljecki, Auteur ; Ken Arroyo Ohori, Auteur ; Jantien E. Stoter, Auteur Année de publication : 2023 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] données localisées 3D [Termes IGN] indicateur spatial [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] morphologie urbaine [Termes IGN] niveau de détail [Termes IGN] Pays-Bas [Termes IGN] SIG 3D Résumé : (auteur) Urban morphology is important in a broad range of investigations across the fields of city planning, transportation, climate, energy, and urban data science. Characterising buildings with a set of numerical metrics is fundamental to studying the urban form. Despite the rapid developments in 3D geoinformation science, and the growing 3D data availability, most studies simplify buildings to their 2D footprint, and when taking their height into account, they at most assume one height value per building, i.e. simple 3D. We take the first step in elevating building metrics into full/true 3D, uncovering the use of higher levels of detail, and taking into account the detailed shape of a building. We set the foundation of the new research line on 3D urban morphology by providing a comprehensive set of 3D metrics, implementing them in openly released software, generating an open dataset containing 2D and 3D metrics for 823,000 buildings in the Netherlands, and demonstrating a use case where clusters and architectural patterns are analysed through time. Our experiments suggest the added value of 3D metrics to complement existing counterparts, reducing ambiguity, and providing advanced insights. Furthermore, we provide a comparative analysis using different levels of detail of 3D building models. Numéro de notice : A2023-076 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2103818 Date de publication en ligne : 01/08/2022 En ligne : https://doi.org/10.1080/13658816.2022.2103818 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101394 [article]

3D building reconstruction from single street view images using deep learning / Hui En Pang in International journal of applied Earth observation and geoinformation, vol 112 (August 2022)  

Public [article]  inInternational journal of applied Earth observation and geoinformation > vol 112 (August 2022) . - n° 102859 Titre : 3D building reconstruction from single street view images using deep learning Type de document : Article/Communication Auteurs : Hui En Pang, Auteur ; Filip Biljecki, Auteur Année de publication : 2022 Article en page(s) : n° 102859 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage profond [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] empreinte [Termes IGN] Helsinki [Termes IGN] image Streetview [Termes IGN] maillage [Termes IGN] morphologie urbaine [Termes IGN] précision géométrique (imagerie) [Termes IGN] reconstruction 3D du bâti [Termes IGN] segmentation d'image [Termes IGN] semis de points Résumé : (auteur) 3D building models are an established instance of geospatial information in the built environment, but their acquisition remains complex and topical. Approaches to reconstruct 3D building models often require existing building information (e.g. their footprints) and data such as point clouds, which are scarce and laborious to acquire, limiting their expansion. In parallel, street view imagery (SVI) has been gaining currency, driven by the rapid expansion in coverage and advances in computer vision (CV), but it has not been used much for generating 3D city models. Traditional approaches that can use SVI for reconstruction require multiple images, while in practice, often only few street-level images provide an unobstructed view of a building. We develop the reconstruction of 3D building models from a single street view image using image-to-mesh reconstruction techniques modified from the CV domain. We regard three scenarios: (1) standalone single-view reconstruction; (2) reconstruction aided by a top view delineating the footprint; and (3) refinement of existing 3D models, i.e. we examine the use of SVI to enhance the level of detail of block (LoD1) models, which are common. The results suggest that trained models supporting (2) and (3) are able to reconstruct the overall geometry of a building, while the first scenario may derive the approximate mass of the building, useful to infer the urban form of cities. We evaluate the results by demonstrating their usefulness for volume estimation, with mean errors of less than 10% for the last two scenarios. As SVI is now available in most countries worldwide, including many regions that do not have existing footprint and/or 3D building data, our method can derive rapidly and cost-effectively the 3D urban form from SVI without requiring any existing building information. Obtaining 3D building models in regions that hitherto did not have any, may enable a number of 3D geospatial analyses locally for the first time. Numéro de notice : A2022-544 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.jag.2022.102859 Date de publication en ligne : 17/06/2022 En ligne : https://doi.org/10.1016/j.jag.2022.102859 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=101160 [article]

GANmapper: geographical data translation / Abraham Noah Wu in International journal of geographical information science IJGIS, vol 36 n° 7 (juillet 2022)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 36 n° 7 (juillet 2022) . - pp 1394 - 1422 Titre : GANmapper: geographical data translation Type de document : Article/Communication Auteurs : Abraham Noah Wu, Auteur ; Filip Biljecki, Auteur Année de publication : 2022 Article en page(s) : pp 1394 - 1422 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie [Termes IGN] apprentissage automatique [Termes IGN] bâtiment [Termes IGN] distance de Fréchet [Termes IGN] empreinte [Termes IGN] morphologie urbaine [Termes IGN] réseau antagoniste génératif [Termes IGN] réseau routier [Termes IGN] système d'information géographique [Termes IGN] texture d'image Résumé : (auteur) We present a new method to create spatial data using a generative adversarial network (GAN). Our contribution uses coarse and widely available geospatial data to create maps of less available features at the finer scale in the built environment, bypassing their traditional acquisition techniques (e.g. satellite imagery or land surveying). In the work, we employ land use data and road networks as input to generate building footprints and conduct experiments in 9 cities around the world. The method, which we implement in a tool we release openly, enables the translation of one geospatial dataset to another with high fidelity and morphological accuracy. It may be especially useful in locations missing detailed and high-resolution data and those that are mapped with uncertain or heterogeneous quality, such as much of OpenStreetMap. The quality of the results is influenced by the urban form and scale. In most cases, the experiments suggest promising performance as the method tends to truthfully indicate the locations, amount, and shape of buildings. The work has the potential to support several applications, such as energy, climate, and urban morphology studies in areas previously lacking required data or inpainting geospatial data in regions with incomplete data. Numéro de notice : A2022-493 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2022.2041643 Date de publication en ligne : 08/03/2022 En ligne : https://doi.org/10.1080/13658816.2022.2041643 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100975 [article]

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The effect of acquisition error and level of detail on the accuracy of spatial analyses / Filip Biljecki in Cartography and Geographic Information Science, Vol 45 n° 2 (March 2018)  

Public [article]  inCartography and Geographic Information Science > Vol 45 n° 2 (March 2018) . - pp 156 - 176 Titre : The effect of acquisition error and level of detail on the accuracy of spatial analyses Type de document : Article/Communication Auteurs : Filip Biljecki, Auteur ; Gerard B.M. Heuvelink, Auteur ; Hugo Ledoux, Auteur ; Jantien E. Stoter, Auteur Année de publication : 2018 Article en page(s) : pp 156 - 176 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] CityGML [Termes IGN] erreur de positionnement [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] niveau de détail [Termes IGN] précision des données [Termes IGN] propagation d'erreur Résumé : (Auteur) There has been a great deal of research about errors in geographic information and how they affect spatial analyses. A typical GIS process introduces various types of errors at different stages, and such errors usually propagate into errors in the result of a spatial analysis. However, most studies consider only a single error type thus preventing the understanding of the interaction and relative contributions of different types of errors. We focus on the level of detail (LOD) and positional error, and perform a multiple error propagation analysis combining both types of error. We experiment with three spatial analyses (computing gross volume, envelope area, and solar irradiation of buildings) performed with procedurally generated 3D city models to decouple and demonstrate the magnitude of the two types of error, and to show how they individually and jointly propagate to the output of the employed spatial analysis. The most notable result is that in the considered spatial analyses the positional error has a much higher impact than the LOD. As a consequence, we suggest that it is pointless to acquire geoinformation of a fine LOD if the acquisition method is not accurate, and instead we advise focusing on the accuracy of the data. Numéro de notice : A2018-008 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2017.1279986 En ligne : https://doi.org/10.1080/15230406.2017.1279986 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88977 [article]

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Level of detail in 3D city models / Filip Biljecki (2017)  

Public Titre : Level of detail in 3D city models Type de document : Thèse/HDR Auteurs : Filip Biljecki, Auteur ; Jantien E. Stoter, Auteur ; Hugo Ledoux, Auteur Editeur : Delft [Pays-Bas] : Delft University of Technology Année de publication : 2017 Note générale : bibliographie Doctoral dissertation, Delft university of technology Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] analyse de sensibilité [Termes IGN] bâtiment [Termes IGN] CityGML [Termes IGN] erreur en position [Termes IGN] modèle 3D de l'espace urbain [Termes IGN] niveau de détail [Termes IGN] propagation d'erreur [Termes IGN] SIG 3D [Termes IGN] spécification Résumé : (auteur) The concept of level of detail (LOD) describes the content of 3D city models and it plays an essential role during their life cycle. On one hand it comes akin to the concepts of scale in cartography and LOD in computer graphics, on the other hand it is a standalone concept that requires attention. LOD has an influence on tendering and acquisition, and it has a hand in storage, maintenance, and application aspects. However, it has not been significantly researched, and this PhD thesis fills this void. This thesis reviews dozens of current LOD standards, revealing that most practitioners consider the LOD to be comprised solely of the geometric detail of data and there are disparate views on the concept as a whole. However, the research suggests that the LOD encompasses additional metrics, such as semantics and texture. The thesis formalises the concept, enabling integration and comparison of current LOD standards. The established framework may be applied to cartography and to different forms of 3D geoinformation such as point clouds. Following the formalised concept, a new LOD specification is presented improving the LOD concept in the current OGC CityGML 2.0 standard, a prominent norm in the 3D GIS industry. The specification introduces 16 LODs for buildings that are shaped after analysing the capabilities of acquisition techniques and a large number of real-world datasets. The improved LOD specification may be integrated in product portfolios and tenders, preventing misunderstandings between stakeholders, and as a better language for communicating the specifics of a dataset to be acquired. The specification also considers different approaches to realise the data. Such geometric references result in dozens of different variants of the same LOD.3D data according to the LOD specification was generated using a procedural modelling engine that was developed over the course of the research. The engine is capable of producing 3D city models in a large number of different variants and according to the CityGML standard. The thesis also catalogues the many different ways to create 3D city models. A prominent technique for producing data in a different LOD is generalisation, i.e. simplifying a 3D city model. The inverse---augmenting the LOD of a dataset---has not been researched to a great extent, and this thesis gives an overview of the topic. This research demonstrates that it is possible to generate 3D city models without elevation measurements, inherently augmenting the LOD of coarser data (2D footprints). The method relies on machine learning: several attributes found in 2D datasets may hint at the height of a building, thus enabling extrusion and creating 3D city models suited for several applications.Some acquisition techniques may result in multi-LOD datasets, and nowadays there are some regions represented in different, independent datasets. However, it was found that possibilities to link such data are deficient. The lack of linking mechanisms inhibits acquisition, storage, and maintenance of multi-LOD data. Two methods for linking features across two or more LODs have been developed resulting in an increased consistency of multi-LOD datasets. The first method links matching geometries across multiple LODs, while the second method establishes a 4D data structure in which the LOD is modelled as the fourth (spatial) dimension.It is often believed that the more detailed 3D data the better. However, similarly as in computer graphics, dealing with data at fine LODs comes at a cost: such datasets are harder to obtain, their storage footprint is large, and their usage within a spatial analysis may be slow. Scarce research has been dedicated to investigating whether an increase in the LOD of the data brings a comparably significant increase in benefits when the data is used in a spatial analysis.First, an analysis using real-world multi-LOD data was carried out. Different LODs of spatial data covering the Netherlands was used in a spatial analysis to refine population maps, obtaining different results for each LOD. However, several problems are exposed, revealing that using real data for such investigations is not optimal.The remainder of the research focuses on using procedurally generated data for such experiments. Synthetic data in several different LODs has been generated and employed for four spatial analyses (estimation of the building shadow, envelope area, volume, and solar irradiation). The experiments result in different conclusions. Finer LODs usually bring some improvement to the quality of the spatial analysis, but not always and such may be negligible. The results of the experiments ultimately depend on the spatial analysis that is considered. The varying results between different spatial analyses make each of them unique. Furthermore, the benefit a finer LOD brings to a spatial analysis is not always clear and easily measurable. In short, striving to produce data at finer LODs may please the eye, but this is not always counter-balanced in the benefit it brings to a spatial analysis.A further addition to the equation above is that when realised, 3D city models are unavoidably burdened with acquisition errors. An error propagation analysis was performed by disturbing the procedurally generated datasets with a range of simulated positional errors. Comparisons have been made between the intentionally degraded datasets and their error-free counterparts, thus obtaining the magnitude of uncertainty the positional errors cause in a spatial analysis. Based on these experiments, several findings are discovered, most importantly:1. How the LODs are realised (which geometric references are used) has a larger influence than the LOD. A coarse LOD produced with a favourable geometric reference may yield better results than a finer LOD realised with an unfavourable reference.2. Positional errors considerably affect spatial analyses. The effect is comparable across similar LODs. Simpler LODs are sligthly less affected by positional errors, but they may contain a large systematic error.3. Errors induced in the acquisition process generally cancel out the improvement provided by finer LODs. The main conclusion is that in the considered spatial analyses the positional error has a significantly higher impact than the LOD. As a consequence, it is suggested that it is pointless to acquire geoinformation at a fine LOD if the acquisition method is not accurate, and instead it is advised to focus on the improvement of accuracy of the data. The thesis proposes additional research for future work. For example, since this research focuses specifically on 3D building models, it would be worth extending the research to other urban features such as roads and vegetation. Furthermore, quality control in 3D GIS does not encompass the evaluation of the LOD of data. Hence integration of the LOD in quality standards should be a priority for future work. Note de contenu : 1- Introduction 2- Background 3- Formalisation of LOD 4- Designing an LOD specification for buildings 5- Variants of LODs 6- Realisation of the specification 7- Generating 3D city models without elevation data 8- Managing multi-LOD data 9- Influence of LOD on spatial analyses (I) 10- Influence of LOD on spatial analyses (II) 11- Sensitivity of LOD to positional errors 12- Combining LOD and positional errors 13- Conclusions and future prospects Numéro de notice : 17541 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : Doctoral dissertation : : Delft university of technology : 2017 DOI : 10.4233/uuid:f12931b7-5113-47ef-bfd4-688aae3be248 En ligne : https://repository.tudelft.nl/islandora/object/uuid%3Af12931b7-5113-47ef-bfd4-68 [...] Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91250

An improved LOD specification for 3D building models / Filip Biljecki in Computers, Environment and Urban Systems, vol 59 (September 2016)  

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A scientometric analysis of selected GIScience journals / Filip Biljecki in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)  

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The variants of an LOD of a 3D building model and their influence on spatial analyses / Filip Biljecki in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)  

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Automatically enhancing CityGML LOD2 models with a corresponding indoor geometry / Roeland Boeters in International journal of geographical information science IJGIS, vol 29 n° 12 (December 2015)  

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