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Termes IGN > mathématiques > statistique mathématique
statistique mathématique
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biométrie,
échantillonnage (statistique), probabilité, statistique. >>Terme(s) spécifique(s) : analyse de régression, analyse de variance, analyse des données, analyse multivariée, analyse séquentielle, calcul d'erreur, carré latin, corrélation (statistique), efficacité asymptotique (statistique), fonction pseudo-aléatoire, loi des grands nombres, modèle linéaire (statistique), modèle non linéaire (statistique), moindre carré, physique statistique, plan d'expérience, rang et sélection (statistique), rupture (statistique), SAS (logiciel), série chronologique, statistique non paramétrique, statistique robuste, tableau de contingence, test d'hypothèses (statistique), statistique stellaire. Equiv. LCSH : Mathematical statistics. Domaine(s) : 510. |
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Object-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)
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[article]
Titre : Object-based random forest modelling of aboveground forest biomass outperforms a pixel-based approach in a heterogeneous and mountain tropical environment Type de document : Article/Communication Auteurs : Eduarda M.O. Silveira, Auteur ; Sérgio Henrique G. Silva, Auteur ; Fausto Weimar Acerbi, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 175 - 188 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse d'image orientée objet
[Termes IGN] biomasse aérienne
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] distribution spatiale
[Termes IGN] forêt équatoriale
[Termes IGN] image Landsat-TM
[Termes IGN] Minas Gerais (Brésil)
[Termes IGN] montagneRésumé : (Auteur) The Brazilian Atlantic Forest is a highly heterogeneous biome of global ecological significance with high levels of terrestrial carbon stocks and aboveground biomass (AGB). Accurate maps of AGB are required for monitoring, reporting, and modelling of forest resources and carbon stocks. Previous research has linked plot-level AGB with environmental and remotely sensed data using pixel-based approaches. However, few studies focused on investigating possible improvements via object-based image analysis (OBIA) including terrain related data to predict AGB in topographically variable and mountainous regions, such as Atlantic forest in Minas Gerais, Brazil. OBIA is expected to reduce known uncertainties related to the positional discrepancy between the image and field data and forest heterogeneity, while terrain derivatives are strong predictors in forest ecosystems driving forest biomass variability. In this research, we compare an object-based approach to a pixel-based method for modeling, mapping and quantifying AGB in the Rio Doce basin, within the Brazilian Atlantic Forest biome. We trained a random forest (RF) machine learning algorithm using environmental, terrain, and Landsat Thematic Mapper (TM) remotely sensed imagery. We aimed to: (i) increase the precision of the AGB estimates; (ii) identify optimal variables that fit the best model, with the lowest root mean square error (RMSE, Mg/ha); (iii) produce an accurate map of the AGB for the study area, and subsequently (iv) describing the AGB spatial distribution as a function of the selected variables. The RF object-based model notably improved the AGB prediction by reducing the mean absolute error (MAE) from 28.64 to 20.95%, and RMSE from 33.43 to 20.08 Mg/ha, and increasing the R² (from 0.57 to 0.86) by using a combination of selected remote sensing, environmental, and terrain variables. Object-based modelling is a promising alternative to common pixel-based approaches to reduce AGB variability in topographically diverse and heterogeneous environments. Investigation of mapped outcomes revealed a decreasing AGB from west towards the east region of the Rio Doce Basin. Over the entire study area, we map a total of 195,799,533 Mg of AGB, ranging from 25.52 to 238 Mg/ha, following seasonal precipitation patterns and anthropogenic disturbance effects. This study provided reliable AGB estimates for the Rio Doce basin, one of the most important watercourses of the globally important Brazilian Atlantic Forest. In conclusion, we highlight that OBIA is a better solution to map forest AGB than the pixel-based traditional method, increasing the precision of AGB estimates in a heterogeneous and mountain tropical environment. Numéro de notice : A2019-230 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jag.2019.02.004 Date de publication en ligne : 15/02/2019 En ligne : https://doi.org/10.1016/j.jag.2019.02.004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92748
in International journal of applied Earth observation and geoinformation > vol 78 (June 2019) . - pp 175 - 188[article]Polarimétrie radar complète et partielle pour le suivi des surfaces terrestres / Pierre-Louis Frison in Revue Française de Photogrammétrie et de Télédétection, n° 219-220 (juin - octobre 2019)
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[article]
Titre : Polarimétrie radar complète et partielle pour le suivi des surfaces terrestres Type de document : Article/Communication Auteurs : Pierre-Louis Frison , Auteur ; Cédric Lardeux, Auteur ; Bénédicte Fruneau
, Auteur ; Jean-Paul Rudant
, Auteur
Année de publication : 2019 Article en page(s) : pp 33 - 39 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications
[Termes IGN] carte de la végétation
[Termes IGN] classification
[Termes IGN] extraction de la végétation
[Termes IGN] image ALOS-PALSAR
[Termes IGN] image radar moirée
[Termes IGN] image Sentinel-SAR
[Termes IGN] polarimétrie radar
[Termes IGN] sédimentation
[Termes IGN] TunisieRésumé : (auteur) This article presents some illustrations of (fully or partial) polarimetric radar data applications for the monitoring of terrestrial surfaces. The first part is dedicated to fully polarimetric radar data. Firstly, a theoretical reminder presents the specificity of fully polarimetric data. Then illustrations are given for vegetation types cartography as well as spatio-temporal processes of sedimentation in a semi-arid area in Tunisia. The second part focuses on partially polarimetric data, of the type acquired by the Sentinel-1A/1B satellite SAR sensors, which will be widely used in future years due to their significant contribution to land surface observations studies for environmental sciences. Numéro de notice : A2019-346 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2019.464 En ligne : https://doi.org/10.52638/rfpt.2019.464 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93383
in Revue Française de Photogrammétrie et de Télédétection > n° 219-220 (juin - octobre 2019) . - pp 33 - 39[article]A regression model-based method for indoor positioning with compound location fingerprints / Tomofumi Takayama in Geo-spatial Information Science, vol 22 n° 2 (June 2019)
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[article]
Titre : A regression model-based method for indoor positioning with compound location fingerprints Type de document : Article/Communication Auteurs : Tomofumi Takayama, Auteur ; Takeshi Umezawa, Auteur ; Nobuyoshi Komuro, Auteur ; Noritaka Osawa, Auteur Année de publication : 2019 Article en page(s) : pp 107 - 113 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement
[Termes IGN] Bluetooth
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] navigation à l'estime
[Termes IGN] positionnement en intérieur
[Termes IGN] régressionRésumé : (Auteur) This paper proposed and evaluated an estimation method for indoor positioning. The method combines location fingerprinting and dead reckoning differently from the conventional combinations. It uses compound location fingerprints, which are composed of radio fingerprints at multiple points of time, that is, at multiple positions, and displacements between them estimated by dead reckoning. To avoid errors accumulated from dead reckoning, the method uses short-range dead reckoning. The method was evaluated using 16 Bluetooth beacons installed in a student room with the dimensions of 11 × 5 m with furniture inside. The Received Signal Strength Indicator (RSSI) values of the beacons were collected at 30 measuring points, which were points at the intersections on a 1 × 1 m grid with no obstacles. A compound location fingerprint is composed of RSSI vectors at two points and a displacement vector between them. Random Forests (RF) was used to build regression models to estimate positions from location fingerprints. The root mean square error of position estimation was 0.87 m using 16 Bluetooth beacons. This error is lower than that received with a single-point baseline model, where a feature vector is composed of only RSSI values at one location. The results suggest that the proposed method is effective for indoor positioning. Numéro de notice : A2019-324 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10095020.2019.1612599 Date de publication en ligne : 17/05/2019 En ligne : https://doi.org/10.1080/10095020.2019.1612599 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93324
in Geo-spatial Information Science > vol 22 n° 2 (June 2019) . - pp 107 - 113[article]Seasonal pattern in time series of variances of GPS residual errors Anova estimates / Darko Anđić in Geodetski vestnik, vol 63 n° 2 (June - August 2019)
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[article]
Titre : Seasonal pattern in time series of variances of GPS residual errors Anova estimates Type de document : Article/Communication Auteurs : Darko Anđić, Auteur Année de publication : 2019 Article en page(s) : pp 260 - 271 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] double différence
[Termes IGN] positionnement par GPS
[Termes IGN] propagation ionosphérique
[Termes IGN] propagation troposphérique
[Termes IGN] rayonnement solaire
[Termes IGN] résidu
[Termes IGN] série temporelle
[Termes IGN] variance
[Termes IGN] variation saisonnièreRésumé : (auteur) In this paper, which represents a continuation of the previous author's work, an inconstancy of GPS residual error ANOVA estimates and their variances are presented. For the purpose of the analysis, fixed solutions for all of the three coordinates, e (eastwards), n (northwards) and u (upwards), obtained by using ionosphere-free (L0) linear combination of double-difference phase observations in the processing of GPS data, were employed. The aim of the research was to consider the behaviour of variances of GPS residual error ANOVA estimates in time because there has not been any paper dealing with that issue so far. Herein, it turned out a seasonal pattern in related time series was present. In addition, it was concluded there was a difference in ANOVA estimate extreme values obtained when one considered daily data subsets compared to those obtained in the approach considering monthly data of the fixed solutions. GPS data collected at ending stations of a baseline of 40 km in length within a four-year period, involving the lowest and increased solar activity, were used in calculations. Numéro de notice : A2019-405 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.15292/geodetski-vestnik.2019.02.260-271 En ligne : http://dx.doi.org/10.15292/geodetski-vestnik.2019.02.260-271 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93509
in Geodetski vestnik > vol 63 n° 2 (June - August 2019) . - pp 260 - 271[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 139-2019021 RAB Revue Centre de documentation En réserve L003 Disponible Semantic façade segmentation from airborne oblique images / Yaping Lin in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 6 (June 2019)
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Titre : Semantic façade segmentation from airborne oblique images Type de document : Article/Communication Auteurs : Yaping Lin, Auteur ; Francesco Nex, Auteur ; Michael Ying Yang, Auteur Année de publication : 2019 Article en page(s) : pp 425 - 433 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse comparative
[Termes IGN] champ aléatoire conditionnel
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] façade
[Termes IGN] image aérienne oblique
[Termes IGN] image RVB
[Termes IGN] segmentation d'image
[Termes IGN] segmentation sémantique
[Termes IGN] semis de pointsRésumé : (Auteur) In this paper, oblique airborne images with very high resolution are used to address the problem from aerial views in urban areas. Traditional classification method (i.e., random forests) is compared with state-of-the-art fully convolutional networks (FCNs). Random forests use hand-craft image features including red, green, blue (RGB), scale-invariant feature transform (SIFT), and Texton, and point cloud features consisting of normal vector and planarity extracted from different scales. In contrast, the inputs of FCNs are the RGB bands and the third components of normal vectors. In both cases, three-dimensional (3D) features are projected back into the image space to support the facade interpretation. Fully connected conditional random field (CRF) is finally taken as a post-processing of the FCN to refine the segmentation results. Several tests have been performed and the achieved results show that the models embedding the 3D component outperform the solution using only images. FCNs significantly outperformed random forests, especially for the balcony delineation. Numéro de notice : A2019-247 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.6.425 Date de publication en ligne : 01/06/2019 En ligne : https://doi.org/10.14358/PERS.85.6.425 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93003
in Photogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 6 (June 2019) . - pp 425 - 433[article]Réservation
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PermalinkAssessing the latest performance of Galileo-only PPP and the contribution of Galileo to Multi-GNSS PPP / Fengyu Xiu in Advances in space research, vol 63 n° 9 (1 May 2019)
PermalinkAutomatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network / Jianfeng Huang in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
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PermalinkDetecting and characterizing downed dead wood using terrestrial laser scanning / Tuomas Yrttimaa in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkEstimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery / Yanan Liu in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
PermalinkExamining the sensitivity of spatial scale in cellular automata Markov chain simulation of land use change / Hao Wu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)
PermalinkExploring the uncertainty of activity zone detection using digital footprints with multi-scaled DBSCAN / Xinyi Liu in International journal of geographical information science IJGIS, Vol 33 n° 5-6 (May - June 2019)
PermalinkFusion of thermal imagery with point clouds for building façade thermal attribute mapping / Dong Lin in ISPRS Journal of photogrammetry and remote sensing, vol 151 (May 2019)
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PermalinkUnderstanding demographic and socioeconomic biases of geotagged Twitter users at the county level / Jiang Juqin in Cartography and Geographic Information Science, vol 46 n° 3 (May 2019)
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PermalinkVoxel-based 3D point cloud semantic segmentation: unsupervised geometric and relationship featuring vs deep learning methods / Florent Poux in ISPRS International journal of geo-information, vol 8 n° 5 (May 2019)
PermalinkReal-time GPS satellite orbit and clock estimation based on OpenMP / Kaifa Kuang in Advances in space research, vol 63 n° 8 (15 April 2019)
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PermalinkIncluding Sentinel-1 radar data to improve the disaggregation of MODIS land surface temperature data / Abdelhakim Amazirh in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)
PermalinkIntegrated relative orientation based on point and line features via Plücker coordinates / Qinghong Sheng in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 4 (avril 2019)
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PermalinkA new relationship between the quality criteria for geodetic networks / Ivandro Klein in Journal of geodesy, vol 93 n° 4 (April 2019)
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PermalinkRefining ionospheric delay modeling for undifferenced and uncombined GNSS data processing / Qile Zhao in Journal of geodesy, vol 93 n° 4 (April 2019)
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PermalinkSegmentation for Object-Based Image Analysis (OBIA): A review of algorithms and challenges from remote sensing perspective / Mohammad D. Hossain in ISPRS Journal of photogrammetry and remote sensing, vol 150 (April 2019)
PermalinkThe process-based forest growth model 3-PG for use in forest management : A review / Rajit Gupta in Ecological modelling, vol 397 (1 April 2019)
PermalinkThe stochastic model for Global Navigation Satellite Systems and terrestrial laser scanning observations: A proposal to account for correlations in least squares adjustment / Gaël Kermarrec in Journal of applied geodesy, vol 13 n° 2 (April 2019)
PermalinkVertical ionospheric delay estimation for single-receiver operation / Ahmed Elsayed in Journal of applied geodesy, vol 13 n° 2 (April 2019)
PermalinkDiscrimination and classification of mangrove forests using EO-1 Hyperion data : a case study of Indian Sundarbans / Tanumi Kumar in Geocarto international, vol 34 n° 4 ([15/03/2019])
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