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Integration of airborne gravimetry data filtering into residual least-squares collocation: example from the 1 cm geoid experiment / Martin Willberg in Journal of geodesy, vol 94 n° 8 (August 2020)
[article]
Titre : Integration of airborne gravimetry data filtering into residual least-squares collocation: example from the 1 cm geoid experiment Type de document : Article/Communication Auteurs : Martin Willberg, Auteur ; Philipp Zingerle, Auteur ; Roland Pail, Auteur Année de publication : 2020 Article en page(s) : n° 75 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique
[Termes IGN] collocation par moindres carrés
[Termes IGN] Colorado (Etats-Unis)
[Termes IGN] filtre passe-bas
[Termes IGN] géoïde gravimétrique
[Termes IGN] géoïde local
[Termes IGN] gravimétrie aérienne
[Termes IGN] levé gravimétrique
[Termes IGN] modèle stochastique
[Termes IGN] pondération
[Termes IGN] processus gaussienRésumé : (auteur) Low-pass filters are commonly used for the processing of airborne gravity observations. In this paper, for the first time, we include the resulting correlations consistently in the functional and stochastic model of residual least-squares collocation. We demonstrate the necessity of removing high-frequency noise from airborne gravity observations, and derive corresponding parameters for a Gaussian low-pass filter. Thereby, we intend an optimal combination of terrestrial and airborne gravity observations in the mountainous area of Colorado. We validate the combination in the frame of our participation in ‘the 1 cm geoid experiment’. This regional geoid modeling inter-comparison exercise allows the calculation of a reference solution, which is defined as the mean value of 13 independent height anomaly results in this area. Our result performs among the best and with 7.5 mm shows the lowest standard deviation to the reference. From internal validation we furthermore conclude that the input from airborne and terrestrial gravity observations is consistent in large parts of the target area, but not necessarily in the highly mountainous areas. Therefore, the relative weighting between these two data sets turns out to be a main driver for the final result, and is an important factor in explaining the remaining differences between various height anomaly results in this experiment. Numéro de notice : A2020-536 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-020-01396-2 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.1007/s00190-020-01396-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95729
in Journal of geodesy > vol 94 n° 8 (August 2020) . - n° 75[article]Los Angeles as a digital place: The geographies of user‐generated content / Andrea Ballatore in Transactions in GIS, Vol 24 n° 4 (August 2020)
[article]
Titre : Los Angeles as a digital place: The geographies of user‐generated content Type de document : Article/Communication Auteurs : Andrea Ballatore, Auteur ; Stefano de Sabbata, Auteur Année de publication : 2020 Article en page(s) : 23 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse spatiale
[Termes IGN] centre urbain
[Termes IGN] contenu généré par les utilisateurs
[Termes IGN] distribution spatiale
[Termes IGN] données multisources
[Termes IGN] données socio-économiques
[Termes IGN] exploration de données géographiques
[Termes IGN] Foursquare
[Termes IGN] Los Angeles
[Termes IGN] modèle de régression
[Termes IGN] OpenStreetMap
[Termes IGN] participation du public
[Termes IGN] représentation géographique
[Termes IGN] réseau social
[Termes IGN] réseau social géodépendant
[Termes IGN] TwitterRésumé : (auteur) Online representations of places are becoming pivotal in informing our understanding of urban life. Content production on online platforms is grounded in the geography of their users and their digital infrastructure. These constraints shape place representation, that is, the amount, quality, and type of digital information available in a geographic area. In this article we study the place representation of user‐generated content (UGC) in Los Angeles County, relating the spatial distribution of the data to its geo‐demographic context. Adopting a comparative and multi‐platform approach, this quantitative analysis investigates the spatial relationship between four diverse UGC datasets and their context at the census tract level (about 685,000 geo‐located tweets, 9,700 Wikipedia pages, 4 million OpenStreetMap objects, and 180,000 Foursquare venues). The context includes the ethnicity, age, income, education, and deprivation of residents, as well as public infrastructure. An exploratory spatial analysis and regression‐based models indicate that the four UGC platforms possess distinct geographies of place representation. To a moderate extent, the presence of Twitter, OpenStreetMap, and Foursquare data is influenced by population density, ethnicity, education, and income. However, each platform responds to different socio‐economic factors and clusters emerge in disparate hotspots. Unexpectedly, Twitter data tend to be located in denser, more deprived areas, and the geography of Wikipedia appears peculiar and harder to explain. These trends are compared with previous findings for the area of Greater London. Numéro de notice : A2020-671 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/SOCIETE NUMERIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12600 Date de publication en ligne : 02/01/2020 En ligne : https://doi.org/10.1111/tgis.12600 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96156
in Transactions in GIS > Vol 24 n° 4 (August 2020) . - 23 p.[article]Assessment of USGS DEMs for modelling pothole inundation in the prairie pothole region of Iowa / Priyadarshi Upadhyay in Geocarto international, vol 35 n° 9 ([01/07/2020])
[article]
Titre : Assessment of USGS DEMs for modelling pothole inundation in the prairie pothole region of Iowa Type de document : Article/Communication Auteurs : Priyadarshi Upadhyay, Auteur ; Amy L. Kaleita, Auteur ; M. L. Soupir, Auteur Année de publication : 2020 Article en page(s) : pp 1018 - 1032 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] données lidar
[Termes IGN] Global Multi-resolution Terrain Elevation Data 2010
[Termes IGN] inondation
[Termes IGN] Iowa (Etats-Unis)
[Termes IGN] mare
[Termes IGN] modèle numérique de surface
[Termes IGN] profondeur
[Termes IGN] semis de pointsRésumé : (auteur) This study aims to compare inundation in two potholes using Annualized Agricultural Non-Point Source Pollution model (AnnAGNPS) with three Digital Elevation Models (DEMs): a 1 m DEM prepared from the LiDAR data which is readily available for the state of Iowa, USGS 1/9 arc-second DEM (∼3 m) which covers about 25% of the conterminous U.S. and USGS 1/3 arc-second DEM (∼10 m) which covers the entire USA. In this study, we found that the variations in water depth and presence/absence of ponding in the potholes of size greater than 1 ha can be predicted using USGS DEMs. The estimates of average water depths using USGS 3 m DEM was found to be 6% and 2% lower than the 1 m LiDAR DEM and the estimates of average water depths using USGS 10 m DEM was found to be 7% and 12% higher than the 1 m LiDAR DEM for the Walnut and Bunny potholes, respectively. Numéro de notice : A2020-429 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1573852 Date de publication en ligne : 06/03/2019 En ligne : https://doi.org/10.1080/10106049.2019.1573852 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95497
in Geocarto international > vol 35 n° 9 [01/07/2020] . - pp 1018 - 1032[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020091 RAB Revue Centre de documentation En réserve L003 Disponible Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation / Michael B. Heflin in Earth and space science, vol 7 n° 7 (July 2020)
[article]
Titre : Automated estimation and tools to extract positions, velocities, breaks, and seasonal terms from daily GNSS measurements: illuminating nonlinear Salton Trough deformation Type de document : Article/Communication Auteurs : Michael B. Heflin, Auteur ; Andrea Donnellan, Auteur ; Jay Parker, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 10 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] chaîne de traitement
[Termes IGN] champ de vitesse
[Termes IGN] déformation horizontale de la croute terrestre
[Termes IGN] données GNSS
[Termes IGN] dorsale
[Termes IGN] faille géologique
[Termes IGN] modèle géologique
[Termes IGN] positionnement par GNSS
[Termes IGN] série temporelle
[Termes IGN] sismologie
[Termes IGN] station GPS
[Termes IGN] valeur aberrante
[Termes IGN] variation saisonnièreRésumé : (auteur) This paper describes the methods used to estimate positions, velocities, breaks, and seasonalterms from daily Global Navigation Satellite System (GNSS) measurements. Break detection and outlierremoval have been automated so that decades of daily measurements from thousands of stations can beprocessed in a few hours. New measurements are added, and parameters are updated every week. Modelparameters allow separation of interseismic, annual, coseismic, and postseismic signals. Tools availablethrough GeoGateway (http://geo-gateway.org) allow rapid visualization and analysis of these terms forresults that can be subsetted in time or space. Results show highly variable and nonlinear motion for GPSstations in southern California. The variable motion is related to seasonal motions, distributed tectonicmotion, earthquakes, and postseismic motions that can continue for years. In some areas results suggest thatadditional processes are responsible for the observed motions. In general, following earthquakes, stationsreturn to their longterm motions after 2–3 years, though some exceptions occur. The use of the tools showsnonlinear motion in the Salton Trough of southern California related to the 2010 M7.2 El MayorCucapahearthquake, 2012 Brawley earthquake swarm, and a creep event on the Superstition Hills fault in 2017. Numéro de notice : A2020-446 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1029/2019EA000644 Date de publication en ligne : 18/05/2020 En ligne : https://doi.org/10.1029/2019EA000644 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95516
in Earth and space science > vol 7 n° 7 (July 2020) . - 10 p.[article]Classification of hyperspectral and LiDAR data using coupled CNNs / Renlong Hang in IEEE Transactions on geoscience and remote sensing, vol 58 n° 7 (July 2020)
[article]
Titre : Classification of hyperspectral and LiDAR data using coupled CNNs Type de document : Article/Communication Auteurs : Renlong Hang, Auteur ; Zhu Li, Auteur ; Pedram Ghamisi, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 4939 - 4950 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] données hétérogènes
[Termes IGN] données lidar
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] fusion de données
[Termes IGN] Houston (Texas)
[Termes IGN] image hyperspectrale
[Termes IGN] occupation du sol
[Termes IGN] Perceptron multicouche
[Termes IGN] précision de la classification
[Termes IGN] semis de points
[Termes IGN] Trente
[Termes IGN] utilisation du solRésumé : (auteur) In this article, we propose an efficient and effective framework to fuse hyperspectral and light detection and ranging (LiDAR) data using two coupled convolutional neural networks (CNNs). One CNN is designed to learn spectral–spatial features from hyperspectral data, and the other one is used to capture the elevation information from LiDAR data. Both of them consist of three convolutional layers, and the last two convolutional layers are coupled together via a parameter-sharing strategy. In the fusion phase, feature-level and decision-level fusion methods are simultaneously used to integrate these heterogeneous features sufficiently. For the feature-level fusion, three different fusion strategies are evaluated, including the concatenation strategy, the maximization strategy, and the summation strategy. For the decision-level fusion, a weighted summation strategy is adopted, where the weights are determined by the classification accuracy of each output. The proposed model is evaluated on an urban data set acquired over Houston, USA, and a rural one captured over Trento, Italy. On the Houston data, our model can achieve a new record overall accuracy (OA) of 96.03%. On the Trento data, it achieves an OA of 99.12%. These results sufficiently certify the effectiveness of our proposed model. Numéro de notice : A2020-391 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.2969024 Date de publication en ligne : 06/02/2020 En ligne : https://doi.org/10.1109/TGRS.2020.2969024 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95374
in IEEE Transactions on geoscience and remote sensing > vol 58 n° 7 (July 2020) . - pp 4939 - 4950[article]Cyclists' exposure to air pollution and noise in Mexico City : contribution of real-time traffic density indicators integrated into GIS / Philippe Apparicio in Revue internationale de géomatique, vol 30 n° 3-4 (juillet - décembre 2020)PermalinkExploratory bivariate and multivariate geovisualizations of a social vulnerability index / Georgianna Strode in Cartographic perspectives, n° 95 (July 2020)PermalinkPredictive land value modelling in Guatemala City using a geostatistical approach and Space Syntax / Jose Morales in International journal of geographical information science IJGIS, vol 34 n° 7 (July 2020)PermalinkA web-based spatial decision support system for monitoring the risk of water contamination in private wells / Yu Lan in Annals of GIS, vol 26 n° 3 (July 2020)PermalinkEvaluating the potential of red spruce (Picea rubens Sarg.) to persist under climate change using historic provenance trials in eastern Canada / Wushuang Li in Forest ecology and management, Vol 466 (15 June 2020)PermalinkUsing machine learning to synthesize spatiotemporal data for modelling DBH-height and DBH-height-age relationships in boreal forests / Jiaxin Chen in Forest ecology and management, Vol 466 (15 June 2020)PermalinkExtracting commuter-specific destination hotspots from trip destination data – comparing the boro taxi service with Citi Bike in NYC / Andreas Keler in Geo-spatial Information Science, vol 23 n° 2 (June 2020)PermalinkAutomatic extraction of road intersection points from USGS historical map series using deep convolutional neural networks / Mahmoud Saeedimoghaddam in International journal of geographical information science IJGIS, vol 34 n° 5 (May 2020)PermalinkDelineating and modeling activity space using geotagged social media data / Lingqian Hu in Cartography and Geographic Information Science, vol 47 n° 3 (May 2020)PermalinkDelineating minor landslide displacements using GPS and terrestrial laser scanning-derived terrain surfaces and trees: a case study of the Slumgullion landslide, Lake City, Colorado / Jin Wang in Survey review, vol 52 n° 372 (May 2020)Permalink