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Space-time multiple regression model for grid-based population estimation in urban areas / Ko Ko Lwin in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)
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Titre : Space-time multiple regression model for grid-based population estimation in urban areas Type de document : Article/Communication Auteurs : Ko Ko Lwin, Auteur ; Komei Sugiura, Auteur ; Koji Zettsu, Auteur Année de publication : 2016 Article en page(s) : pp 1579 - 1593 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] appareil portable
[Termes IGN] densité de population
[Termes IGN] estimation statistique
[Termes IGN] milieu urbain
[Termes IGN] modèle conceptuel de données spatio-temporelles
[Termes IGN] population
[Termes IGN] régression multiple
[Termes IGN] TwitterRésumé : (Auteur) We can collect, store, and analyze a huge amount of information about human mobility and social interaction activities due to the emergence of information and communication technologies and location-enabled mobile devices under cyber physical system frameworks. The high spatial resolution of population data on a multi-temporal scale is required by transport planners, human geographers, social scientists, and emergency management teams. In this study, we build a space-time multiple regression model to estimate grid-based (500 m × 500 m) spatial resolution at multi-temporal scale (30-min intervals) population data based on the space-time relationship among geospatially enabled person trip (PT) survey data and incorporate both mobile call (MC) and geotagged Twitter (GT) data. Since using geospatially enabled PT survey data as dependent variables enables us to acquire actual population amounts, which strongly depend on MCs and social interaction activities. Although many grids have a strong correlation between PT and MC/GT, some show fewer correlation results, especially where the grids have factories, schools, and workshops in which fewer MCs are found but a large population is presented. Although GT data are sparser than MCs, people from amusement and tourist areas can be detected by GT data. The space-time multiple regression model can also estimate the different amounts of populations based on human travel behavior that changes over space and time. According to accuracy assessments, the night-time estimated results, especially between 00:00 and 06:30, strongly correlate with national census data except in places where the grids have railway and subway stations. Numéro de notice : A2016-319 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1143099 En ligne : http://dx.doi.org/10.1080/13658816.2016.1143099 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80939
in International journal of geographical information science IJGIS > vol 30 n° 7- 8 (July - August 2016) . - pp 1579 - 1593[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016042 RAB Revue Centre de documentation En réserve L003 Disponible 079-2016041 RAB Revue Centre de documentation En réserve L003 Disponible Stochastic modeling of triple-frequency BeiDou signals: estimation, assessment and impact analysis / Bofeng Li in Journal of geodesy, vol 90 n° 7 (July 2016)
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Titre : Stochastic modeling of triple-frequency BeiDou signals: estimation, assessment and impact analysis Type de document : Article/Communication Auteurs : Bofeng Li, Auteur Année de publication : 2016 Article en page(s) : pp 593 – 610 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] données BeiDou
[Termes IGN] erreur instrumentale
[Termes IGN] modèle stochastique
[Termes IGN] orbite géostationnaire
[Termes IGN] positionnement par GNSS
[Termes IGN] récepteur trifréquence
[Termes IGN] résolution d'ambiguïtéRésumé : (auteur) Stochastic models are important in global navigation satellite systems (GNSS) estimation problems. One can achieve reliable ambiguity resolution and precise positioning only by use of a suitable stochastic model. The BeiDou system has received increased research focus, but based only on empirical stochastic models from the knowledge of GPS. In this paper, we will systematically study the estimation, assessment and impacts of a triple-frequency BeiDou stochastic model. In our estimation problem, a single-difference, geometry-free functional model is used to extract pure random noise. A very sophisticated structure of unknown variance matrix is designed to allow the estimation of satellite-specific variances, cross correlations between two arbitrary frequencies, as well as the time correlations for phase and code observations per frequency. In assessing the stochastic models, six data sets with four brands of BeiDou receivers on short and zero-length baselines are processed, and the results are compared. In impact analysis of stochastic model, the performance of integer ambiguity resolution and positioning are numerically demonstrated using a realistic stochastic model. The results from ultrashort (shorter than 10 m) and zero-length baselines indicate that BeiDou stochastic models are affected by both observation and receiver brands. The observation variances have been modeled by an elevation-dependent function, but the modeling errors for geostationary earth orbit (GEO) satellites are larger than for inclined geosynchronous satellite orbit (IGSO) and medium earth orbit (MEO) satellites. The stochastic model is governed by both the internal errors of the receiver and external errors at the site. Different receivers have different capabilities for resisting external errors. A realistic stochastic model is very important for achieving ambiguity resolution with a high success rate and small false alarm and for determining realistic variances for position estimates. To the best of our knowledge, this paper is the first comprehensive study on such stochastic models used specifically with BeiDou data. Numéro de notice : A2016-424 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0896-7 En ligne : http://dx.doi.org/10.1007/s00190-016-0896-7 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81318
in Journal of geodesy > vol 90 n° 7 (July 2016) . - pp 593 – 610[article]Comparison of robust estimators for leveling networks in Monte Carlo simulations / Maria Pokarowska in Reports on geodesy and geoinformatics, vol 101 (June 2016)
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Titre : Comparison of robust estimators for leveling networks in Monte Carlo simulations Type de document : Article/Communication Auteurs : Maria Pokarowska, Auteur Année de publication : 2016 Article en page(s) : pp 70 - 81 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Nivellement
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] méthode des moindres carrés
[Termes IGN] méthode robuste
[Termes IGN] réseau de nivellement
[Termes IGN] valeur aberranteRésumé : (Auteur) We compared the method of least squares (LS), Pope’s iterative data snooping (IDS) and Huber’s M-estimator (HU) in realistic leveling networks, for which the heights or the vertical displacements of points are known. The study was conducted using the Monte Carlo simulation, in which one repeatedly generates sets of observations related to the measurement data, then calculates values of the estimators and, finally, assesses it with respect to the real coordinates. To simulate outliers we used popular mixture models with two or more normal distributions. It is shown that for small, strong networks robust methods IDS and HU are more accurate than LS, but for large, weak networks occurring in practice there is no significant difference between the considered methods in the accuracy of the solution. Numéro de notice : A2016-653 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/rgg-2016-0023 En ligne : http://dx.doi.org/10.1515/rgg-2016-0023 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81872
in Reports on geodesy and geoinformatics > vol 101 (June 2016) . - pp 70 - 81[article]Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods / X. Tang in Annals of forest research, vol 59 n° 2 (July - December 2016)
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Titre : Inventory-based estimation of forest biomass in Shitai County, China: A comparison of five methods Type de document : Article/Communication Auteurs : X. Tang, Auteur ; L. Fehrmann, Auteur ; Fengying Guan, Auteur ; David I. Forrester, Auteur ; R. Guisasola, Auteur ; C. Kleinn, Auteur Année de publication : 2016 Article en page(s) : pp 269 - 280 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] Abies (genre)
[Termes IGN] biomasse forestière
[Termes IGN] Chine
[Termes IGN] estimation statistique
[Termes IGN] feuillu
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] puits de carbone
[Vedettes matières IGN] Ecologie forestièreRésumé : (auteur) Several comparative studies have reported that there can be great discrepancies between different methods used to estimate forest biomass. With the development of carbon markets, an accurate estimation at the regional scale (i.e. county level) is becoming increasingly important for local government. In this study, we applied five methodologies [continuous biomass expansion factor (CBEF) approach, mean biomass density (MB) approach, mean biomass expansion factor (MBEF) approach, national continuous biomass expansion factors (NCBEF) proposed by Fang et al (2002), standard IPCC approach] to estimate the total biomass for Shitai County, China. The CBEF is generally considered to provide the most realistic estimates in term of regional biomass because CBEF reflects the change of BEF to stand density, stand age and site conditions. The forests of the whole county were divided into four forest types, namely Chinese fir plantations (CF), hardwood broadleaved forests (HB), softwood–broadleaved forests (SB) and mason pine forests (MP) according to the local forest management inventory of 2004. Generally, the MBEF approach overestimated forest biomass while the IPCC approach underestimated forest biomass for all forest types when CBEF derived biomass was used as a control. The MB approach provided the most similar biomass estimates for all forest types and could be an alternative approach when a CBEF equation is lacking in the study area. The total biomass derived from MBEF was highest at 1.44×107 t, followed by 1.32 ×107 t from CBEF, 1.31 ×107 t from NCBEF, 1.25 ×107 t from MB and 1.16 ×107 t from IPCC. Our results facilitate method selection for regional forest biomass estimation and provide statistical evidence for local government planning to enter the potential carbon market. Numéro de notice : A2016--095 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.15287/afr.2016.574 En ligne : http://doi.org/10.15287/afr.2016.574 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84647
in Annals of forest research > vol 59 n° 2 (July - December 2016) . - pp 269 - 280[article]The variants of an LOD of a 3D building model and their influence on spatial analyses / Filip Biljecki in ISPRS Journal of photogrammetry and remote sensing, vol 116 (June 2016)
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Titre : The variants of an LOD of a 3D building model and their influence on spatial analyses Type de document : Article/Communication Auteurs : Filip Biljecki, Auteur ; Hugo Ledoux, Auteur ; Jantien E. Stoter, Auteur ; M. George Vosselman, Auteur Année de publication : 2016 Article en page(s) : pp 42 – 54 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] analyse spatiale
[Termes IGN] CityGML
[Termes IGN] cohérence géométrique
[Termes IGN] méthode de Monte-Carlo
[Termes IGN] niveau de détail
[Termes IGN] reconstruction 3D du bâti
[Termes IGN] SIG 3DRésumé : (auteur) The level of detail (LOD) of a 3D city model indicates the model’s grade and usability. However, there exist multiple valid variants of each LOD. As a consequence, the LOD concept is inconclusive as an instruction for the acquisition of 3D city models. For instance, the top surface of an LOD1 block model may be modelled at the eaves of a building or at its ridge height. Such variants, which we term geometric references, are often overlooked and are usually not documented in the metadata. Furthermore, the influence of a particular geometric reference on the performance of a spatial analysis is not known.
In response to this research gap, we investigate a variety of LOD1 and LOD2 geometric references that are commonly employed, and perform numerical experiments to investigate their relative difference when used as input for different spatial analyses. We consider three use cases (estimation of the area of the building envelope, building volume, and shadows cast by buildings), and compute the deviations in a Monte Carlo simulation.
The experiments, carried out with procedurally generated models, indicate that two 3D models representing the same building at the same LOD, but modelled according to different geometric references, may yield substantially different results when used in a spatial analysis. The outcome of our experiments also suggests that the geometric reference may have a bigger influence than the LOD, since an LOD1 with a specific geometric reference may yield a more accurate result than when using LOD2 models.Numéro de notice : A2016-577 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2016.03.003 En ligne : https://doi.org/10.1016/j.isprsjprs.2016.03.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81709
in ISPRS Journal of photogrammetry and remote sensing > vol 116 (June 2016) . - pp 42 – 54[article]Generative models for road network reconstruction / Colin Kuntzsch in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
PermalinkReconstruction of itineraries from annotated text with an informed spanning tree algorithm / Ludovic Moncla in International journal of geographical information science IJGIS, vol 30 n° 5-6 (May - June 2016)
PermalinkA correctly weighted least squares adjustment - Part 3 Estimating standard errors in angular observations / Charles D. Ghilani in xyHt, vol 2016 n° 4 (April 2016)
PermalinkJoint analysis of GOCE gravity gradients data of gravitational potential and of gravity with seismological and geodynamic observations to infer mantle properties / Marianne Greff-Lefftz in Geophysical journal international, vol 205 n° 1 (April 2016)
PermalinkAn average error-ellipsoid model for evaluating TLS point-cloud accuracy / Xijiang Chen in Photogrammetric record, vol 31 n° 153 (March - May 2016)
PermalinkApproximating prediction uncertainty for random forest regression models / John W. Coulston in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 3 (March 2016)
PermalinkMarkov random field-based method for super-resolution mapping of forest encroachment from remotely sensed ASTER image / L. K. Tiwari in Geocarto international, vol 31 n° 3 - 4 (March - April 2016)
PermalinkMIDAS robust trend estimator for accurate GPS station velocities without step detection / Geoffrey Blewitt in Journal of geophysical research : Solid Earth, vol 121 n° 3 (March 2016)
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PermalinkRobust spatial approximation of laser scanner point clouds by means of Free-form Curve approaches in deformation analysis / Johannes Bureick in Journal of applied geodesy, vol 10 n° 1 (March 2016)
PermalinkA correctly weighted least squares adjustment - Part 2 Estimating uncertainties / Charles D. Ghilani in xyHt, vol 2016 n° 2 (February 2016)
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