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Progressive TIN densification with connection analysis for urban Lidar data / Tao Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 3 (March 2021)
[article]
Titre : Progressive TIN densification with connection analysis for urban Lidar data Type de document : Article/Communication Auteurs : Tao Wang, Auteur ; Lianbin Deng, Auteur ; Yuhong Li, Auteur ; Hao Peng, Auteur Année de publication : 2021 Article en page(s) : pp 205 - 213 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] pente
[Termes IGN] semis de points
[Termes IGN] Triangulated Irregular NetworkRésumé : (Auteur) Urban lidar data are advantageous for capturing the terrain surface of built-up areas, which can be directly used to provide digital surface models. Cloud points are classified into ground points to obtain digital terrain models. This study proposes a method to improve the progressive triangulated irregular network (TIN ) densification method using a TIN connection analysis algorithm, namely, connection analysis via slope analysis. The proposed method comprises five steps: selection of seed points, connection and slope analysis, increasing the seed points, construction of the TIN model of the seed points, and an iterative construction of the final TIN. Seven data sets from the International Society for Photogrammetry and Remote Sensing Working Group are used to test whether the proposed method can preserve discontinuities of landscapes and reduce omission and total errors by an average of 9% and 5%, respectively; achieving such results can reduce the amount of workload required for result modification during posttreatment, thus decreasing costs. Numéro de notice : A2021-243 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.87.3.207 Date de publication en ligne : 01/03/2021 En ligne : https://doi.org/10.14358/PERS.87.3.207 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97291
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 3 (March 2021) . - pp 205 - 213[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 105-2021031 SL Revue Centre de documentation Revues en salle Disponible Assessing spatial-temporal evolution processes and driving forces of karst rocky desertification / Fei Chen in Geocarto international, vol 36 n° 3 ([15/02/2021])
[article]
Titre : Assessing spatial-temporal evolution processes and driving forces of karst rocky desertification Type de document : Article/Communication Auteurs : Fei Chen, Auteur ; Shijie Wang, Auteur ; Xiaoyong Bai, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 262 - 280 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse spatio-temporelle
[Termes IGN] carte d'utilisation du sol
[Termes IGN] Chine
[Termes IGN] classification et arbre de régression
[Termes IGN] désertification
[Termes IGN] données spatiotemporelles
[Termes IGN] image Landsat-OLI
[Termes IGN] image Landsat-TM
[Termes IGN] karst
[Termes IGN] lithologieRésumé : (auteur) Karst Rocky Desertification (KRD) has become the most serious ecological disaster in Southwest China. We used the data of Thematic Mapper (TM) images from 1990, 1995, 2000, 2004, and 2011 and the 2016 Operational Land Imager (OLI) image. These sensing images were pre-processed by removing non-karst areas based on lithology and cutting away the land types impossibly generating KRD from land use maps. Then, we used a Classification And Regression Tree (CART) to classify the KRD. We want to improve the interpretation accuracy of KRD through the above steps. The results were as follows: (1) The KRD experiences the evolution process of ‘first deterioration and then improvement’. The rate is −4.94 km2.a−1 over a period of 1990 to 2004, and the rate is 36.48 km2.a−1 from 2004 to 2016; (2) The most influential factors causing KRD formation are the lithology and the resident population density, with contribution rates of 30.17% and 25.86%, respectively. Numéro de notice : A2021-140 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1595175 Date de publication en ligne : 18/07/2019 En ligne : https://doi.org/10.1080/10106049.2019.1595175 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97036
in Geocarto international > vol 36 n° 3 [15/02/2021] . - pp 262 - 280[article]A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping / Zhice Fang in International journal of geographical information science IJGIS, vol 35 n° 2 (February 2021)
[article]
Titre : A comparative study of heterogeneous ensemble-learning techniques for landslide susceptibility mapping Type de document : Article/Communication Auteurs : Zhice Fang, Auteur ; Yi Wang, Auteur ; Ling Peng, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 321 - 347 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] effondrement de terrain
[Termes IGN] géomorphologie locale
[Termes IGN] pondération
[Termes IGN] régression logistique
[Termes IGN] réseau neuronal récurrent
[Termes IGN] risque naturelRésumé : (auteur) This study introduces four heterogeneous ensemble-learning techniques, that is, stacking, blending, simple averaging, and weighted averaging, to predict landslide susceptibility in Yanshan County, China. These techniques combine several state-of-the-art classifiers of convolutional neural network, recurrent neural network, support vector machine, and logistic regression in specific ways to produce reliable results and avoid problems with the model selection. The study consists of three main steps. The first step establishes a spatial database consisting of 16 landslide conditioning factors and 380 historical landslide locations. The second step randomly selects training (70% of the total) and test (30%) datasets out of grid cells corresponding to landslide and non-slide locations in the study area. The final step constructs the proposed heterogeneous ensemble-learning methods for landslide susceptibility mapping. The proposed ensemble-learning methods show higher prediction accuracy than the individual classifiers mentioned above based on statistical measures. The blending ensemble-learning method achieves the highest overall accuracy of 80.70% compared to the other ensemble-learning methods. Numéro de notice : A2021-028 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1808897 Date de publication en ligne : 15/09/2020 En ligne : https://doi.org/10.1080/13658816.2020.1808897 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96704
in International journal of geographical information science IJGIS > vol 35 n° 2 (February 2021) . - pp 321 - 347[article]Geomorphology and (palaeo-)hydrography of the Southern Atbai plain and western Eritrean Highlands (Eastern Sudan/Western Eritrea) / Stefano Costanzo in Journal of maps, vol 17 n° 2 (February 2021)
[article]
Titre : Geomorphology and (palaeo-)hydrography of the Southern Atbai plain and western Eritrean Highlands (Eastern Sudan/Western Eritrea) Type de document : Article/Communication Auteurs : Stefano Costanzo, Auteur ; Andrea Zerboni, Auteur ; Mauro Cremaschi, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 51 - 62 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Cartographie thématique
[Termes IGN] analyse du paysage
[Termes IGN] carte géomorphologique
[Termes IGN] ère quaternaire
[Termes IGN] Erythrée
[Termes IGN] hydrographie
[Termes IGN] montagne
[Termes IGN] roche
[Termes IGN] Sahel
[Termes IGN] Soudan
[Termes IGN] tectoniqueRésumé : (auteur) We present the geomorphology of the Southern Atbai Plain (Eastern Sudan) and the western edge of the Eritrean Highlands (Western Eritrea), in the eastern Sahel. The mountainous area consists of Paleo-Proterozoic gneiss and Neo-Proterozoic igneous rocks and meta-volcanic assemblages shaped as inselbergs and whaleback landforms by weathering. Bare-rock hills emerge from a gentle glacis that oversees the Southern Atbai alluvial plain, located between the Atbara and Gash Rivers. The plain features the SSE-NNW-oriented endorheic terminal fan of the Gash River and is crossed by intricate Early to Late Pleistocene paleochannels, whose evolution was controlled by the interplay between Quaternary regional tectonics and arid to humid climatic and environmental oscillations. The map is intended to interpret the evolution of local landscape, thus representing a tool for reconstructing the spatial and temporal distribution of Late Quaternary archaeological features and their functional relationships with the fossil fluvial system and the western foothills. Numéro de notice : A2021-201 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1869112 Date de publication en ligne : 17/01/2021 En ligne : https://doi.org/10.1080/17445647.2020.1869112 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97156
in Journal of maps > vol 17 n° 2 (February 2021) . - pp 51 - 62[article]Monitoring the coastal changes of the Po river delta (Northern Italy) since 1911 using archival cartography, multi-temporal aerial photogrammetry and LiDAR data: implications for coastline changes in 2100 A.D. / Massimo Fabris in Remote sensing, Vol 13 n° 3 (February 2021)
[article]
Titre : Monitoring the coastal changes of the Po river delta (Northern Italy) since 1911 using archival cartography, multi-temporal aerial photogrammetry and LiDAR data: implications for coastline changes in 2100 A.D. Type de document : Article/Communication Auteurs : Massimo Fabris, Auteur Année de publication : 2021 Article en page(s) : n° 529 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse spatio-temporelle
[Termes IGN] archives
[Termes IGN] cartographie ancienne
[Termes IGN] détection de changement
[Termes IGN] données lidar
[Termes IGN] données multitemporelles
[Termes IGN] modèle numérique de terrain
[Termes IGN] montée du niveau de la mer
[Termes IGN] photogrammétrie aérienne
[Termes IGN] Pô (delta)
[Termes IGN] semis de points
[Termes IGN] surveillance du littoral
[Termes IGN] trait de côteRésumé : (auteur) Interaction between land subsidence and sea level rise (SLR) increases the hazard in coastal areas, mainly for deltas, characterized by flat topography and with great social, ecological, and economic value. Coastal areas need continuous monitoring as a support for human intervention to reduce the hazard. Po River Delta (PRD, northern Italy) in the past was affected by high values of artificial land subsidence: even if at low rates, anthropogenic settlements are currently still in progress and produce an increase of hydraulic risk due to the loss of surface elevation both of ground and levees. Many authors have provided scenarios for the next decades with increased flooding in densely populated areas. In this work, a contribution to the understanding future scenarios based on the morphological changes that occurred in the last century on the PRD coastal area is provided: planimetric variations are reconstructed using two archival cartographies (1911 and 1924), 12 multi-temporal high-resolution aerial photogrammetric surveys (1933, 1944, 1949, 1955, 1962, 1969, 1977, 1983, 1990, 1999, 2008, and 2014), and four LiDAR (light detection and ranging) datasets (acquired in 2006, 2009, 2012, and 2018): obtained results, in terms of emerged surfaces variations, are linked to the available land subsidence rates (provided by leveling, GPS—global positioning system, and SAR—synthetic aperture radar data) and to the expected SLR values, to perform scenarios of the area by 2100: results of this work will be useful to mitigate the hazard by increasing defense systems and preventing the risk of widespread flooding. Numéro de notice : A2021-199 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13030529 Date de publication en ligne : 02/02/2021 En ligne : https://doi.org/10.3390/rs13030529 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97151
in Remote sensing > Vol 13 n° 3 (February 2021) . - n° 529[article]A regional spatiotemporal analysis of large magnitude snow avalanches using tree rings / Erich Peitzsch in Natural Hazards and Earth System Sciences, Vol 21 n° 2 (February 2021)PermalinkTopoclimatic zoning of continental Chile / Donna Cortez in Journal of maps, vol 17 n° 2 (February 2021)PermalinkUsing automated vegetation cover estimation from close-range photogrammetric point clouds to compare vegetation location properties in mountain terrain / R. Niederheiser in GIScience and remote sensing, vol 58 n° 1 (February 2021)PermalinkUsing Sentinel-2 images to estimate topography, tidal-stage lags and exposure periods over large intertidal areas / José P. 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Simões in Geocarto international, vol 35 n° 11 ([01/08/2020])PermalinkSize dependency of variables influencing fire occurrence in Mediterranean forests of Eastern Spain / Marina Peris-Llopis in European Journal of Forest Research, vol 139 n°4 (August 2020)PermalinkTourism land use simulation for regional tourism planning using POIs and cellular automata / Hong Shi in Transactions in GIS, Vol 24 n° 4 (August 2020)PermalinkCan we characterize river corridor evolution at a continental scale from historical topographic maps? A first assessment from the comparison of four countries / J. Horacio Garcia in River Research and Applications, vol 36 n° 6 (July 2020)PermalinkPath length correction for improving leaf area index measurements over sloping terrains: A deep analysis through computer simulation / Gaofei Yin in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)PermalinkCoastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) / Yawo Konko in Advances in Remote Sensing, vol 9 n° 2 (June 2020)PermalinkData-driven evidential belief function (EBF) model in exploring landslide susceptibility zones for the Darjeeling Himalaya, India / Subrata Mondal in Geocarto international, Vol 35 n° 8 ([01/06/2020])PermalinkImproved optical image matching time series inversion approach for monitoring dune migration in North Sinai Sand Sea: Algorithm procedure, application, and validation / Eslam Ali in ISPRS Journal of photogrammetry and remote sensing, vol 164 (June 2020)PermalinkMountain summit detection with Deep Learning: evaluation and comparison with heuristic methods / Rocio Nahime Torres in Applied geomatics, vol 12 n° 2 (June 2020)PermalinkExploring the potential of deep learning segmentation for mountain roads generalisation / Azelle Courtial in ISPRS International journal of geo-information, vol 9 n° 5 (May 2020)PermalinkGeomorphic Change Detection Using Cost-Effective Structure-from-Motion Photogrammetry: Evaluation of Direct Georeferencing from Consumer-Grade UAS at Orewa Beach (New Zealand) / Stéphane Bertin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 5 (May 2020)PermalinkIntertidal topography mapping using the waterline method from Sentinel-1 & -2 images: The examples of Arcachon and Veys Bays in France / Edward Salameh in ISPRS Journal of photogrammetry and remote sensing, vol 163 (May 2020)PermalinkAnalytic hierarchy process based spatial biodiversity impact assessment model of highway broadening in Sikkim Himalaya / Polash Banerjee in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkMonitoring of landslide activity at the Sirobagarh landslide, Uttarakhand, India, using LiDAR, SAR interferometry and geodetic surveys / Ashutosh Tiwari in Geocarto international, vol 35 n° 5 ([01/04/2020])PermalinkLe sol s'affaisse, l'eau monte [Delta du Gange-Brahmapoutre-Meghna] / Marielle Mayo in Géomètre, n° 2179 (avril 2020)PermalinkTemporal Validation of Four LAI Products over Grasslands in the Northeastern Tibetan Plateau / Gaofei Yin in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 4 (April 2020)PermalinkComparison of spatial modelling approaches to simulate urban growth: a case study on Udaipur city, India / Biswajit Mondal in Geocarto international, vol 35 n° 4 ([15/03/2020])PermalinkDimension reduction methods applied to coastline extraction on hyperspectral imagery / Ozan Arslan in Geocarto international, vol 35 n° 4 ([15/03/2020])Permalink3D laser scanning of the natural caves: Example of Škocjanske jame / Richard Walters in Geodetski vestnik, Vol 64 n° 1 (March - May 2020)PermalinkAssessment of salt marsh change on Assateague Island National Seashore between 1962 and 2016 / Anthony Campbell in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 3 (March 2020)PermalinkClassifying physiographic regimes on terrain and hydrologic factors for adaptive generalization of stream networks / Lauwrence V. 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Does it affect the DEM accuracy? / Sandra Bujan in Photogrammetric record, vol 34 n° 167 (September 2019)PermalinkTopographie et archéologie, du cordeau au tout numérique : plus de 40 ans d'interactions / Bertrand Chazaly in XYZ, n° 160 (septembre 2019)PermalinkValidating the use of object-based image analysis to map commonly recognized landform features in the United States / Samantha T. Arundel in Cartography and Geographic Information Science, Vol 46 n° 5 (September 2019)PermalinkIntegration of corner reflectors for the monitoring of mountain glacier areas with Sentinel-1 time series / Matthias Jauvin in Remote sensing, vol 11 n° 8 (August 2019)PermalinkLarge scale semi-automatic detection of forest roads from low density LiDAR data on steep terrain in Northern Spain / Convadonga Prendes in iForest, biogeosciences and forestry, vol 12 n° 4 (July 2019)PermalinkPotential of crowdsourced data for integrating landmarks and routes for rescue in mountain areas / Marie-Dominique Van Damme in International journal of cartography, vol 5 n° 2-3 (July - November 2019)PermalinkDéveloppement d’un « ModelBuilder » pour l’évaluation de la recharge nette : cas de la nappe phréatique de Zéramdine Beni Hassène (Tunisie) / Imen Hentati in Géomatique expert, n° 128 (juin - juillet 2019)PermalinkObject-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment / Eduarda M.O. Silveira in International journal of applied Earth observation and geoinformation, vol 78 (June 2019)PermalinkCoastline extraction from SAR images using robust ridge tracing / Dailiang Wang in Marine geodesy, vol 42 n° 3 (May 2019)PermalinkCartographie de l’aléa érosif dans le bassin sud du Litani-Liban / Hussein El Hage Hassan in Revue internationale de géomatique, vol 29 n° 2 (avril - juin 2019)PermalinkAnalysis of ocean tide loading displacements by GPS kinematic precise point positioning: a case study at the China coastal site SHAO / H. Zhao in Survey review, vol 51 n° 365 (March 2019)Permalink