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Detecting classic Maya settlements with Lidar-derived relief visualizations / Amy E. Thompson in Remote sensing, vol 12 n° 17 (September - 1 2020)  

Public [article]  inRemote sensing > vol 12 n° 17 (September - 1 2020) . - 29 p. Titre : Detecting classic Maya settlements with Lidar-derived relief visualizations Type de document : Article/Communication Auteurs : Amy E. Thompson, Auteur Année de publication : 2020 Article en page(s) : 29 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] analyse d'image orientée objet [Termes descripteurs IGN] Belize [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] fouille archéologique [Termes descripteurs IGN] modèle numérique de terrain [Termes descripteurs IGN] relief [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] site archéologique Résumé : (auteur) In the past decade, Light Detection and Ranging (lidar) has fundamentally changed our ability to remotely detect archaeological features and deepen our understanding of past human-environment interactions, settlement systems, agricultural practices, and monumental constructions. Across archaeological contexts, lidar relief visualization techniques test how local environments impact archaeological prospection. This study used a 132 km2 lidar dataset to assess three relief visualization techniques—sky-view factor (SVF), topographic position index (TPI), and simple local relief model (SLRM)—and object-based image analysis (OBIA) on a slope model for the non-automated visual detection of small hinterland Classic (250–800 CE) Maya settlements near the polities of Uxbenká and Ix Kuku’il in Southern Belize. Pedestrian survey in the study area identified 315 plazuelas across a 35 km2 area; the remaining 90 km2 in the lidar dataset is yet to be surveyed. The previously surveyed plazuelas were compared to the plazuelas visually identified on the TPI and SLRM. In total, an additional 563 new possible plazuelas were visually identified across the lidar dataset, using TPI and SLRM. Larger plazuelas, and especially plazuelas located in disturbed environments, are often more likely to be detected in a visual assessment of the TPI and SLRM. These findings emphasize the extent and density of Classic Maya settlements and highlight the continued need for pedestrian survey to ground-truth remotely identified archaeological features and the impact of modern anthropogenic behaviors for archaeological prospection. Remote sensing and lidar have deepened our understanding of past human settlement systems and low-density urbanism, processes that we experience today as humans residing in modern cities Numéro de notice : A2020-598 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.3390/rs12172838 date de publication en ligne : 01/09/2020 En ligne : https://doi.org/10.3390/rs12172838 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95944 [article]

Recognition of building group patterns using graph convolutional network / Rong Zhao in Cartography and Geographic Information Science, Vol 47 n° 5 (September 2020)  

Public [article]  inCartography and Geographic Information Science > Vol 47 n° 5 (September 2020) . - pp 400 - 417 Titre : Recognition of building group patterns using graph convolutional network Type de document : Article/Communication Auteurs : Rong Zhao, Auteur ; Tinghua Ai, Auteur ; Wenhao Yu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 400 - 417 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] classification par réseau neuronal convolutif [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] espace urbain [Termes descripteurs IGN] généralisation du bâti [Termes descripteurs IGN] graphe [Termes descripteurs IGN] modélisation du bâti [Termes descripteurs IGN] reconnaissance de formes Résumé : (auteur) Recognition of building group patterns is of great significance for understanding and modeling the urban space. However, many current methods cannot fully utilize spatial information and have trouble efficiently dealing with topographic data with high complexity. The design of intelligent computational models that can act directly on topographic data to extract spatial features is critical. To this end, we propose a novel deep neural network based on graph convolutions to automatically identify building group patterns with arbitrary forms. The method first models buildings by a general graph, and then the neural network simultaneously learns the structural information as well as vertex attributes to classify building objects. We apply this method to real building data, and the experimental results show that the proposed method can effectively capture spatial information to make more accurate predictions than traditional methods. Numéro de notice : A2020-510 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2020.1757512 date de publication en ligne : 12/06/2020 En ligne : https://doi.org/10.1080/15230406.2020.1757512 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95663 [article]

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Methodology of the automatic generalization of buildings, road networks, forests and surface waters: a case study based on the Topographic Objects Database in Poland / Izabela Karsznia in Geocarto international, vol 35 n° 7 ([15/05/2020])  

Public [article]  inGeocarto international > vol 35 n° 7 [15/05/2020] . - pp 735 - 758 Titre : Methodology of the automatic generalization of buildings, road networks, forests and surface waters: a case study based on the Topographic Objects Database in Poland Type de document : Article/Communication Auteurs : Izabela Karsznia, Auteur ; Marta Przychodzeń, Auteur ; Karolina Sielicka, Auteur Année de publication : 2020 Article en page(s) : pp 735 - 758 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] ArcGIS [Termes descripteurs IGN] base de connaissances [Termes descripteurs IGN] base de données orientée objet [Termes descripteurs IGN] bâtiment [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] eau de surface [Termes descripteurs IGN] forêt [Termes descripteurs IGN] placement automatique des objets [Termes descripteurs IGN] Pologne [Termes descripteurs IGN] réseau routier [Vedettes matières IGN] Généralisation Résumé : (auteur) This research presents the formalization and verification of the methodology for the automatic generalization of buildings, road networks, forests and surface waters from the Topographic Objects Database (BDOT10k) in Poland. The article makes the following contributions. First, the generalization methodology contained in the official documents was acquired and presented in the form of the knowledge base. Second, the possibilities and limitations of the implementation of the knowledge base in ArcGIS were discussed. Third, the suitability of the BDOT10k structure for the purpose of automatic generalization performance was verified. As a result of the conducted generalization tests, it was found that the formalization and implementation of the methodology contained in the official specifications, in the automatic mode are not entirely possible. The generalization results, however, are promising. The presented research is in line with the studies recently conducted not only by Polish but also other European National Mapping Agencies. Numéro de notice : A2020-271 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1533591 date de publication en ligne : 03/12/2018 En ligne : https://doi.org/10.1080/10106049.2018.1533591 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95055 [article]

Recognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation / Xianjin He in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 14 p. Titre : Recognizing linear building patterns in topographic data by using two new indices based on Delaunay triangulation Type de document : Article/Communication Auteurs : Xianjin He, Auteur ; Min Deng, Auteur Année de publication : 2020 Article en page(s) : 14 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique [Termes descripteurs IGN] adjacence [Termes descripteurs IGN] direction [Termes descripteurs IGN] discontinuité [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] modèle linéaire [Termes descripteurs IGN] modèle numérique du bâti [Termes descripteurs IGN] reconnaissance de formes [Termes descripteurs IGN] segmentation [Termes descripteurs IGN] triangulation de Delaunay [Termes descripteurs IGN] voisinage (topologie) Résumé : (auteur) Building pattern recognition is fundamental to a wide range of downstream applications, such as urban landscape evaluation, social analyses, and map generalization. Although many studies have been conducted, there is still a lack of satisfactory results, due to the imprecision of the relative direction model of any two adjacent buildings and the ineffective extraction methods. This study aims to provide an alternative for quantifying the direction and the spatial continuity of any two buildings on the basis of the Delaunay triangulation for the recognition of linear building patterns. First, constrained Delaunay triangulations (CDTs) are created for all buildings within each block and every two adjacent buildings. Then, the spatial continuity index (SCI), the direction index (DI), and other spatial relations (e.g., distance) of every two adjacent buildings are derived using the CDT. Finally, the building block is modelled as a graph based on derived matrices, and a graph segmentation approach is proposed to extract linear building patterns. In the segmentation process, the edges of the graph are removed first, according to the global thresholds of the SCI and distance, and are subsequently subdivided into subgraphs on direction rules. The proposed method is tested using three datasets. The experimental results suggest that the proposed method can recognize both collinear and curvilinear building patterns, given that the correctness values are all above 92% for the three study areas. The results also demonstrate that the novel SCI can effectively filter many insignificant neighbor relationships in the graph segmentation process. It is noteworthy that the proposed DI is capable of measuring building relative directions accurately and works efficiently in linear building pattern extraction. Numéro de notice : A2020-267 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040231 date de publication en ligne : 09/04/2020 En ligne : https://doi.org/10.3390/ijgi9040231 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95031 [article]

Recent sea level change in the black sea from satellite altimetry and tide gauge observations / Nevin Betül Avsar in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 18 p. Titre : Recent sea level change in the black sea from satellite altimetry and tide gauge observations Type de document : Article/Communication Auteurs : Nevin Betül Avsar, Auteur ; H.S. Kutoglu, Auteur Année de publication : 2020 Article en page(s) : 18 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] altimétrie [Termes descripteurs IGN] changement du niveau de la mer [Termes descripteurs IGN] déformation verticale de la croute terrestre [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] données satellitaires [Termes descripteurs IGN] données topographiques [Termes descripteurs IGN] érosion côtière [Termes descripteurs IGN] marégraphe [Termes descripteurs IGN] Noire, mer [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] surcharge hydrologique [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) Global mean sea level has been rising at an increasing rate, especially since the early 19th century in response to ocean thermal expansion and ice sheet melting. The possible consequences of sea level rise pose a significant threat to coastal cities, inhabitants, infrastructure, wetlands, ecosystems, and beaches. Sea level changes are not geographically uniform. This study focuses on present-day sea level changes in the Black Sea using satellite altimetry and tide gauge data. The multi-mission gridded satellite altimetry data from January 1993 to May 2017 indicated a mean rate of sea level rise of 2.5 ± 0.5 mm/year over the entire Black Sea. However, when considering the dominant cycles of the Black Sea level time series, an apparent (significant) variation was seen until 2014, and the rise in the mean sea level has been estimated at about 3.2 ± 0.6 mm/year. Coastal sea level, which was assessed using the available data from 12 tide gauge stations, has generally risen (except for the Bourgas Station). For instance, from the western coast to the southern coast of the Black Sea, in Constantza, Sevastopol, Tuapse, Batumi, Trabzon, Amasra, Sile, and Igneada, the relative rise was 3.02, 1.56, 2.92, 3.52, 2.33, 3.43, 5.03, and 6.94 mm/year, respectively, for varying periods over 1922–2014. The highest and lowest rises in the mean level of the Black Sea were in Poti (7.01 mm/year) and in Varna (1.53 mm/year), respectively. Measurements from six Global Navigation Satellite System (GNSS) stations, which are very close to the tide gauges, also suggest that there were significant vertical land movements at some tide gauge locations. This study confirmed that according to the obtained average annual phase value of sea level observations, seasonal sea level variations in the Black Sea reach their maximum annual amplitude in May–June. Numéro de notice : A2020-254 Affiliation des auteurs : non IGN Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9030185 date de publication en ligne : 20/03/2020 En ligne : https://doi.org/10.3390/ijgi9030185 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95008 [article]

High‐resolution national land use scenarios under a shrinking population in Japan / Haruka Ohashi in Transactions in GIS, vol 23 n° 4 (August 2019)  

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Quantification of airborne lidar accuracy in coastal dunes (Fire Island, New York) / William J. Schmelz in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 2 (February 2019)  

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Machine learning and geographic information systems for large-scale mapping of renewable energy potential / Dan Assouline (2019)  

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Geospatial data on the web / Linda Van Den Brink (2018)    

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Production de données topographiques de référence de l'Eurométropole de Strasbourg / Olivier Banaszak in XYZ, n° 153 (décembre 2017 - février 2018)  

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Predicting palustrine wetland probability using random forest machine learning and digital elevation data-derived terrain variables / Aaron E. Maxwell in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 6 (June 2016)  

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Qualification de la précision de données topographiques issues d’acquisitions par méthode scanner laser dynamique ferroporté / Audrey Jacquin in XYZ, n° 146 (mars - mai 2016)

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Application of topo-edaphic factors and remotely sensed vegetation indices to enhance biomass estimation in a heterogeneous landscape in the Eastern Arc mountains of Tanzania / Mercy Ojoyi in Geocarto international, vol 31 n° 1 - 2 (January - February 2016)  

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Intégration de données topographiques dans un SIG dans le cadre du décret DT-DICT (2ème partie) / Michaël Prévieu in Géomatique expert, n° 106 (septembre - octobre 2015)

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Cartographie des végétations herbacées des marais littoraux à partir de données topographiques LiDAR / Sébastien Rapinel in Revue Française de Photogrammétrie et de Télédétection, n° 210 (Avril 2015)

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