Centre de documentation
scientifique

Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data / Timo P Pitkänen in ISPRS Journal of photogrammetry and remote sensing, vol 130 (August 2017)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 130 (August 2017) . - pp 150 - 161 Titre : Reducing classification error of grassland overgrowth by combing low-density lidar acquisitions and optical remote sensing data Type de document : Article/Communication Auteurs : Timo P Pitkänen, Auteur ; Niina Käyhkö, Auteur Année de publication : 2017 Article en page(s) : pp 150 - 161 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques [Termes IGN] analyse diachronique [Termes IGN] arbre (flore) [Termes IGN] boisement naturel [Termes IGN] carte de la végétation [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] densité des points [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] erreur de classification [Termes IGN] image Landsat [Termes IGN] orthoimage [Termes IGN] prairie [Termes IGN] structure de données localisées Résumé : (Auteur) Mapping structural changes in vegetation dynamics has, for a long time, been carried out using satellite images, orthophotos and, more recently, airborne lidar acquisitions. Lidar has established its position as providing accurate material for structure-based analyses but its limited availability, relatively short history, and lack of spectral information, however, are generally impeding the use of lidar data for change detection purposes. A potential solution in respect of detecting both contemporary vegetation structures and their previous trajectories is to combine lidar acquisitions with optical remote sensing data, which can substantially extend the coverage, span and spectral range needed for vegetation mapping. In this study, we tested the simultaneous use of a single low-density lidar data set, a series of Landsat satellite frames and two high-resolution orthophotos to detect vegetation succession related to grassland overgrowth, i.e. encroachment of woody plants into semi-natural grasslands. We built several alternative Random Forest models with different sets of variables and tested the applicability of respective data sources for change detection purposes, aiming at distinguishing unchanged grassland and woodland areas from overgrown grasslands. Our results show that while lidar alone provides a solid basis for indicating structural differences between grassland and woodland vegetation, and orthophoto-generated variables alone are better in detecting successional changes, their combination works considerably better than its respective parts. More specifically, a model combining all the used data sets reduces the total error from 17.0% to 11.0% and omission error of detecting overgrown grasslands from 56.9% to 31.2%, when compared to model constructed solely based on lidar data. This pinpoints the efficiency of the approach where lidar-generated structural metrics are combined with optical and multitemporal observations, providing a workable framework to identify structurally oriented and dynamically organized landscape phenomena, such as grassland overgrowth. Numéro de notice : A2017-513 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.05.016 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.05.016 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86459 [article]

Exemplaires(3)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
081-2017081	RAB	Revue	Centre de documentation	En réserve L003	Disponible
081-2017083	DEP-EXM	Revue	LASTIG	Dépôt en unité	Exclu du prêt
081-2017082	DEP-EAF	Revue	Nancy	Dépôt en unité	Exclu du prêt

Querying visible points in large obstructed space / Jianqiu Xu in Geoinformatica, vol 19 n° 3 (July - September 2015)  

Public [article]  inGeoinformatica > vol 19 n° 3 (July - September 2015) . - pp 435 - 461 Titre : Querying visible points in large obstructed space Type de document : Article/Communication Auteurs : Jianqiu Xu, Auteur ; Ralf Hartmut Güting, Auteur Année de publication : 2015 Article en page(s) : pp 435 - 461 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] base de données localisées [Termes IGN] géomètrie algorithmique [Termes IGN] noeud [Termes IGN] performance [Termes IGN] point d'intérêt [Termes IGN] structure de données localisées [Termes IGN] traitement automatique de données [Termes IGN] traitement de données localisées [Termes IGN] triangulation (topologie) Résumé : (auteur) Querying visible points is a fundamental problem in computational geometry and spatial databases. With the development of new applications such as trip planning and nearest neighbors, querying visible points plays a key role in obstacle space and the result can be further used such as defining the shortest path. Thereby, efficiently finding the result is essentially important. However, the performance of current methods decrease substantially for large datasets. To solve the problem, we proposes a new and fast algorithm to find visible points for an arbitrary query location inside a large polygon containing obstacles. The method is based on polygon triangulation. By decomposing the polygon into a set of triangles, we manage the polygon by organizing triangles in an efficient way instead of maintaining a large number of vertices. We propose a data structure to partition the searching space into several parts, each of which is independently processed. Afterwards, by recursively calling a method we search visible points by accessing triangles and return the result in a progressive way. Through a theoretical analysis, assuming the polygon contains N vertices in total, the time complexity of our algorithm is O(N), improving the existing method O(N l o g N). We prove the correctness of the algorithm and analyze the space complexity, which is O(N). The technique is extended to return visible points less than a threshold distance to the query location. Using both synthetic and real datasets, we perform extensive experiments to test our algorithm and demonstrate its efficiency and effectiveness. Visible points are efficiently processed in a large obstacle space with over one million vertices. Experimental results show that our technique gains more than one order of magnitude speedup compared to competitive methods using large datasets. Numéro de notice : A2015-495 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-014-0213-7 Date de publication en ligne : 15/08/2014 En ligne : https://doi.org/10.1007/s10707-014-0213-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77307 [article]

An evaluation and classification of nD topological data structures for the representation of objects in a higher-dimensional GIS / Ken Arroyo Ohori in International journal of geographical information science IJGIS, vol 29 n° 5 (May 2015)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 29 n° 5 (May 2015) . - pp 825 - 849 Titre : An evaluation and classification of nD topological data structures for the representation of objects in a higher-dimensional GIS Type de document : Article/Communication Auteurs : Ken Arroyo Ohori, Auteur ; Hugo Ledoux, Auteur ; Jantien E. Stoter, Auteur Année de publication : 2015 Article en page(s) : pp 825 - 849 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes IGN] base de données multidimensionnelles [Termes IGN] base de données spatiotemporelles [Termes IGN] classification [Termes IGN] données spatiotemporelles [Termes IGN] évaluation des données [Termes IGN] implémentation (informatique) [Termes IGN] intégration de données [Termes IGN] modèle topologique de données [Termes IGN] relation topologique [Termes IGN] structure de données localisées [Termes IGN] système d'information géographique Résumé : (Auteur) One solution to the integration of additional characteristics, e.g. time and scale, into geographic information system (GIS) datasets is to model them as extra geometric dimensions perpendicular to the spatial ones, creating a higher-dimensional model. Previous work has been mostly limited to higher-dimensional rasters and hierarchies of trees, which grow exponentially with the dimension. As representations with limited topological relationships quickly become intractable in higher dimensions, a topological vector approach seems most suitable for this purpose, requiring the use of higher-dimensional topological data structures. We therefore present in this paper an evaluation and classification of the possible data structures for an nD GIS, including how they can be implemented to support real-world data aspects, such as holes, disconnected components and attributes, as well as practical issues that affect their feasibility, like the availability of algorithms, libraries and software. Numéro de notice : A2015-594 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2014.999683 En ligne : https://doi.org/10.1080/13658816.2014.999683 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=77884 [article]

Abstracting geographic information in a data rich world / Dirk Burghardt (2014)

Public Titre : Abstracting geographic information in a data rich world : Methodologies and applications of map generalisation Type de document : Monographie Auteurs : Dirk Burghardt, Éditeur scientifique ; Cécile Duchêne , Éditeur scientifique ; William A Mackaness, Éditeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2014 Collection : Lecture notes in Geoinformation and Cartography, ISSN 1863-2246 Importance : 408 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-319-00202-6 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] généralisation cartographique automatisée [Termes IGN] généralisation de base de données [Termes IGN] intégration de données [Termes IGN] spécification de contenu [Termes IGN] structure de données localisées [Termes IGN] système d'information géographique [Vedettes matières IGN] Généralisation Résumé : (Editeur) Research in the field of automated generalisation has faced new challenges in recent years as a result of technological developments in web-based processing, new visualisation paradigms and access to very large volumes of multi-source data generated by sensors and humans. In these contexts, map generalisation needs to underpin ‘on-demand mapping’, a form of mapping that responds to individual user requirements in the thematic selection and visualisation of geographic information. It is this new impetus that drives the research of the ICA Commission on Generalisation and Multiple Representation (for example through its annual workshops, biannual tutorials and publications in international journals). This book has a coherent structure, each chapter focusing on core concepts and tasks in the map generalisation towards on-demand mapping. Each chapter presents a state-of-the-art review, together with case studies that illustrate the application of pertinent generalisation methodologies. The book addresses issues from data gathering to multi scaled outputs. Thus there are chapters devoted to defining user requirements in handling specifications, and in the application and evaluation of map generalisation algorithms. It explores the application of generalisation methodologies in the context of growing volumes of data and the increasing popularity of user generated content. Note de contenu : 1. Map Generalisation: Fundamental to the Modelling and Understanding of Geographic Space. 2. Map Specifications and User Requirements. 3. Modelling Geographic Relationships in Automated Environments 4. Data Structures for Continuous Generalisation: tGAP and SSC. 5. Integrating and Generalising Volunteered Geographic Information 6. Generalisation Operators 7. Process Modelling, Web Services and Geoprocessing. 8. Terrain Generalisation. 9. Evaluation in Generalisation 10. Generalisation in the Context of Schematised Maps 11. Generalisation in Practice Within National Mapping Agencies 12. Conclusion: Major Achievements and Research Challenges in Generalisation Numéro de notice : 22152 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif nature-HAL : DirectOuvrColl/Actes DOI : 10.1007/978-3-319-00203-3 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=73835

Contient

• Abstracting geographic information in a data rich world, ch. 1. Map generalisation: fundamental to the modelling and understanding of geographic space / William A Mackaness (2014)  
• Abstracting geographic information in a data rich world, ch. 2. Map specifications and user requirements / Sandrine Balley (2014)  
• Abstracting geographic information in a data rich world, ch. 3. Modelling geographic relationships in automated environments / Guillaume Touya (2014)  
• Abstracting geographic information in a data rich world, ch. 7. Process modelling, web services and geoprocessing / Nicolas Regnauld (2014)  
• Abstracting geographic information in a data rich world, ch. 11. Generalisation in practice within national mapping agencies / Cécile Duchêne (2014)  
• Abstracting geographic information in a data rich world, ch. 12. Conclusion: major achievements and research challenges in generalisation / Dirk Burghardt (2014)  

Exemplaires(2)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
22152-01	37.10	Livre	Centre de documentation	Géomatique	Disponible
22152-02	37.10	Livre	Centre de documentation	Géomatique	Disponible

Out-of-core GPU-based change detection in massive 3D point clouds / Rico Richter in Transactions in GIS, vol 17 n° 5 (October 2013)  

Public [article]  inTransactions in GIS > vol 17 n° 5 (October 2013) . - pp 724 - 741 Titre : Out-of-core GPU-based change detection in massive 3D point clouds Type de document : Article/Communication Auteurs : Rico Richter, Auteur ; Jan Eric Kiprianidis, Auteur ; Jürgen Döllner, Auteur Année de publication : 2013 Article en page(s) : pp 724 - 741 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] attribut [Termes IGN] détection de changement [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] processeur graphique [Termes IGN] semis de points [Termes IGN] structure de données localisées [Termes IGN] visualisation 3D [Termes IGN] visualisation simultanée Résumé : (Auteur) If sites, cities, and landscapes are captured at different points in time using technology such as LiDAR, large collections of 3D point clouds result. Their efficient storage, processing, analysis, and presentation constitute a challenging task because of limited computation, memory, and time resources. In this work, we present an approach to detect changes in massive 3D point clouds based on an out-of-core spatial data structure that is designed to store data acquired at different points in time and to efficiently attribute 3D points with distance information. Based on this data structure, we present and evaluate different processing schemes optimized for performing the calculation on the CPU and GPU. In addition, we present a point-based rendering technique adapted for attributed 3D point clouds, to enable effective out-of-core real-time visualization of the computation results. Our approach enables conclusions to be drawn about temporal changes in large highly accurate 3D geodata sets of a captured area at reasonable preprocessing and rendering times. We evaluate our approach with two data sets from different points in time for the urban area of a city, describe its characteristics, and report on applications. Numéro de notice : A2013-579 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/j.1467-9671.2012.01362.x Date de publication en ligne : 05/12/2012 En ligne : https://doi.org/10.1111/j.1467-9671.2012.01362.x Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32715 [article]

Real-time generalization of point data in mobile and web mapping using quadtrees / Pia Bereuter in Cartography and Geographic Information Science, vol 40 n° 4 (September 2013)  

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Retour d’expérience sur la restructuration d’un SIG et la diffusion des données dans le cadre de la directive INSPIRE : Comment utiliser la directive INSPIRE à l’échelle d’un SIG historique pour en assurer la refonte ? / C. Devaux (01/09/2011)

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Modelling and analysing 3D buildings with a primal/dual data structure / P. Boguslawski in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 2 (March - April 2011)  

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A multiple representation data structure for dynamic visualisation of generalised 3D city models / B. Mao in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 2 (March - April 2011)  

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vol 66 n° 2 - March - April 2011 - Quality, scale and analysis aspects of urban city models (Bulletin de ISPRS Journal of photogrammetry and remote sensing) / Monika Sester  

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Variable-scale Geo-information / Martijn Meijers (2011)  

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Géodécisionnel : y'en a pour tous les goûts / Françoise de Blomac in SIG la lettre, n° 120 (octobre 2010)

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The FOSS4G 2010 conference: fitting a global trend / J. Ticheler in Geoinformatics, vol 13 n° 7 (01/10/2010)

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Assessing spatial data infrastructures / Lucasz Grus (2010)  

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A network representation of raster land-cover patches / L. De Cola in Photogrammetric Engineering & Remote Sensing, PERS, vol 76 n° 1 (January 2010)  

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