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Automatic delineation of built-up area at urban block level from topographic maps / Sebastian Muhs in Computers, Environment and Urban Systems, vol 58 (July 2016)  

Public [article]  inComputers, Environment and Urban Systems > vol 58 (July 2016) . - pp 71 - 84 Titre : Automatic delineation of built-up area at urban block level from topographic maps Type de document : Article/Communication Auteurs : Sebastian Muhs, Auteur ; Hendrik Herold, Auteur ; Gotthard Meinel, Auteur ; Dirk Burghardt, Auteur ; Odette Kretschmer, Auteur Année de publication : 2016 Article en page(s) : pp 71 - 84 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse d'image numérique [Termes IGN] base de données historiques [Termes IGN] carte topographique [Termes IGN] détection du bâti [Termes IGN] extraction semi-automatique [Termes IGN] îlot urbain [Termes IGN] vision par ordinateur [Termes IGN] zone urbaine Résumé : (auteur) To comprehensively study and better understand urban dynamic processes — such as densification, growth and sprawl, or shrinkage — spatio-temporal databases that allow to track changes of geographic objects like buildings and urban blocks are essential. While comprehensive databases exist for contemporary data, they usually lack a historic dimension. The manual constitution of historic geographic data, be it based on historic maps or aerial images, is a time consuming and laborious process, however. Therefore, we present an approach to semi-automatically extract this data from binary topographic maps with regard to built-up areas at urban block level. The suitability of topographic maps for historic urban analysis has been proven in previous research. To overcome the challenges that are inherent in scanned topographic maps in regard to digital image interpretation we designed a modular process. Among others, these challenges include fused and (multi-)fragmented map objects caused by the overlap of competing content layers in one single binary map. After a preliminary separation of individual map object layers from the map content, the process follows a two-stage top-down approach. At first, the map is organized into street blocks, which after that are re-delineated in regard to built-up area. In doing so, we achieve correctness values ranging from 0.97 to 0.93 for three study sites in Germany. With an increasing number of projects that provide historic topographic maps as georeferenced digital data, our process represents a promising approach to efficiently prepare these historic data for integration into a spatio-temporal database with minimal user intervention. Numéro de notice : A2016-404 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.compenvurbsys.2016.04.001 En ligne : http://dx.doi.org/10.1016/j.compenvurbsys.2016.04.001 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81221 [article]

Automatic identification of building types based on topographic databases – a comparison of different data sources / Robert Hecht in International journal of cartography, vol 1 n° 1 (August 2015)  

Public [article]  inInternational journal of cartography > vol 1 n° 1 (August 2015) . - pp 18 - 31 Titre : Automatic identification of building types based on topographic databases – a comparison of different data sources Type de document : Article/Communication Auteurs : Robert Hecht, Auteur ; Gotthard Meinel, Auteur ; Manfred F. Buchroithner, Auteur Année de publication : 2015 Article en page(s) : pp 18 - 31 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées [Termes IGN] apprentissage automatique [Termes IGN] base de données topographiques [Termes IGN] bâtiment [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] emprise au sol [Termes IGN] généralisation cartographique automatisée [Termes IGN] identification automatique [Termes IGN] reconnaissance de formes Résumé : (auteur) Data, maps and services of the national mapping and cadastral agencies contain geometric information on buildings, particularly building footprints. However, building type information is often not included. In this paper, we propose a data-driven approach for automatic classification of building footprints that make use of pattern recognition and machine learning techniques. Using a Random Forest Classifier the suitability of five different data sources (e.g. topographic raster maps, cadastral databases or digital landscape models) is investigated with respect to the achieved accuracies. The results of this study show that building footprints obtained from topographic databases such as digital landscape models, cadastral databases or 3D city models can be classified with an accuracy of 90–95%. When classifying building footprints on the basis of topographic maps the accuracy is considerably lower (as of 76–88%). The automatic classification of building footprints provides an important contribution to the acquisition of new small-scale indicators on settlement structure, such as building density, floor space ratio or dwelling/population densities. In addition to its importance for urban research and planning, the results are also relevant for cartographic disciplines, such as map generalization, automated mapping and geovisualization. Numéro de notice : A2015-434 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/23729333.2015.1055644 En ligne : https://doi.org/10.1080/23729333.2015.1055644 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=76883 [article]

Land-use monitoring by topographic data analysis / Tobias Krüger in Cartography and Geographic Information Science, vol 40 n° 3 (June 2013)  

Public [article]  inCartography and Geographic Information Science > vol 40 n° 3 (June 2013) . - pp 220 - 228 Titre : Land-use monitoring by topographic data analysis Type de document : Article/Communication Auteurs : Tobias Krüger, Auteur ; Gotthard Meinel, Auteur ; Ulrich Schumacher, Auteur Année de publication : 2013 Article en page(s) : pp 220 - 228 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de données [Termes IGN] base de données topographiques [Termes IGN] indicateur [Termes IGN] surveillance de l'urbanisation [Termes IGN] utilisation du sol [Termes IGN] visualisation cartographique Résumé : (Auteur) The rate of land consumption is an important factor to be considered within policies on sustainable land use aiming to reduce demand for settlement and traffic areas. As an expression of the political intent to achieve sustainable development, the German government announced to reduce the consumption of open space for settlement or transportation infrastructure significantly by 2020. Progress toward such specific goals can, of course, only be monitored if planning authorities are supplied with up-to-date and precise information on land use. This article presents one approach to the calculation of trends in land use that uses geoprocessing of topographic base data. Among the advantages of this approach are the nationwide availability of data with homogeneous quality and regular mandatory updating by surveying authorities. The spatial analysis of topographic base data is currently a highly automated process, which means geoprocessing procedures can be repeated regularly in order to realize time series. Such systematic monitoring of land use is undertaken by the project Monitor of Settlement and Open Space Development (IOER Monitor). By mid-2013, the fourth time period based on data from 2012 will be available online, ensuring that information on a wide range of land-use types is provided for a time series beginning back in 2006. Thus, the IOER Monitor is a convenient tool for the analysis and monitoring of land use for all administrative units ranging from German municipalities (approximately 12,000 in number) to the country as a whole, as well as for raster cells ranging from 100 m to 10 km. Numéro de notice : A2013-755 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2013.809232 En ligne : https://doi.org/10.1080/15230406.2013.809232 Format de la ressource électronique : url Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32891 [article]

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