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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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Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency / Jiaqi Tian in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)
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Titre : Improving the accuracy of spring phenology detection by optimally smoothing satellite vegetation index time series based on local cloud frequency Type de document : Article/Communication Auteurs : Jiaqi Tian, Auteur ; Xiaolin Zhu, Auteur ; Jin Chen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 29 - 44 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Enhanced vegetation index
[Termes IGN] filtrage du bruit
[Termes IGN] image Terra-MODIS
[Termes IGN] indice de végétation
[Termes IGN] lissage de données
[Termes IGN] nébulosité
[Termes IGN] phénologie
[Termes IGN] série temporelleRésumé : (auteur) Vegetation phenology can be extracted from vegetation index (VI) time series of satellite data. The maximum value composite (MVC) procedure and smoothing filters have been conventionally used as standard methods to exclude noises in the VI time series before extracting the vegetation phenology [e.g., National Aeronautics and Space Administration (NASA) VNP22Q2 and United States Geological Survey (USGS) MCD12Q2 phenology products]. However, it is unclear how to optimize the MVC and smoothing filters to produce the most accurate phenology metrics given that cloud frequency varies spatially. This study designed two simulation experiments, namely (1) using only the MVC and (2) using the MVC and smoothing filters together to smooth the enhanced vegetation index (EVI) time series for detecting spring phenology, i.e., start of season (SOS), over the northern hemisphere (north of 30°N) on a 5° × 5° grid cell basis by the inflection point and relative threshold algorithms. The results revealed that (1) the inappropriate selection of MVC periods (e.g., too short or too long) affected the accuracy of the SOS extracted by both phenology detection algorithms; (2) a filtering process with optimal parameters can reduce the effects of the MVC period on SOS extraction to a considerable extent, i.e., 65% and 61% for iterative Savitzky–Golay (SG) and penalized cubic splines (SP) filters, respectively; (3) optimal parameters for both the MVC and smoothing filters showed significant spatial heterogeneity; and (4) validation with ground PhenoCam data indicated that optimal parameters of the MVC and smoothing filters can produce more accurate results than official vegetation phenology products that use uniform parameters. Specifically, the R2 values of the NASA product and the USGS product were 0.58 and 0.67, which were increased to 0.70 and 0.81, respectively, by the optimal smoothing process. Optimal parameters of the MVC and smoothing filters provided by this study in each 5° × 5° sub-region may help future studies to improve the accuracy of phenology detection from satellite VI time series. Numéro de notice : A2021-653 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2021.08.003 Date de publication en ligne : 14/08/2021 En ligne : https://doi.org/10.1016/j.isprsjprs.2021.08.003 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98383
in ISPRS Journal of photogrammetry and remote sensing > vol 180 (October 2021) . - pp 29 - 44[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021101 SL Revue Centre de documentation Revues en salle Disponible 081-2021103 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021102 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Landslide susceptibility prediction based on image semantic segmentation / Bowen Du in Computers & geosciences, vol 155 (October 2021)
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Titre : Landslide susceptibility prediction based on image semantic segmentation Type de document : Article/Communication Auteurs : Bowen Du, Auteur ; Zirong Zhao, Auteur ; Xiao Hu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 104860 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] aléa
[Termes IGN] apprentissage automatique
[Termes IGN] Chine
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] effondrement de terrain
[Termes IGN] image captée par drone
[Termes IGN] modèle de simulation
[Termes IGN] prévention des risques
[Termes IGN] segmentation sémantiqueRésumé : (auteur) Numéro de notice : A2021-683 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1016/j.cageo.2021.104860 Date de publication en ligne : 16/06/2021 En ligne : https://doi.org/10.1016/j.cageo.2021.104860 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98408
in Computers & geosciences > vol 155 (October 2021) . - n° 104860[article]Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing / Radhika Ravi in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)
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Titre : Least squares adjustment with a rank-deficient weight matrix and Its applicability to image/Lidar data processing Type de document : Article/Communication Auteurs : Radhika Ravi, Auteur ; Ayman Habib, Auteur Année de publication : 2021 Article en page(s) : pp 717 - 733 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] alignement des données
[Termes IGN] chevauchement
[Termes IGN] compensation par moindres carrés
[Termes IGN] données lidar
[Termes IGN] lidar mobile
[Termes IGN] matrice
[Termes IGN] matrice de covariance
[Termes IGN] modèle de Gauss-Helmert
[Termes IGN] modèle de Gauss-Markov
[Termes IGN] modèle mathématique
[Termes IGN] modélisation 3D
[Termes IGN] pondération
[Termes IGN] semis de pointsRésumé : (Auteur) This article proposes a solution to special least squares adjustment (LSA) models with a rank-deficient weight matrix, which are commonly encountered in geomatics. The two sources of rank deficiency in weight matrices are discussed: naturally occurring due to the inherent characteristics of LSA mathematical models and artificially induced to eliminate nuisance parameters from LSA estimation. The physical interpretation of the sources of rank deficiency is demonstrated using a case study to solve the problem of 3D line fitting, which is often encountered in geomatics but has not been addressed fully to date. Finally, some geomatics-related applications—mobile lidar system calibration, point cloud registration, and single-photo resection—are discussed along with respective experimental results, to emphasize the need to assess LSA models and their weight matrices to draw inferences regarding the effective contribution of observations. The discussion and results demonstrate the vast applications of this research in geomatics as well as other engineering domains. Numéro de notice : A2021-675 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.20-00081R3 Date de publication en ligne : 10/01/2021 En ligne : https://doi.org/10.14358/PERS.20-00081R3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98861
in Photogrammetric Engineering & Remote Sensing, PERS > vol 87 n° 10 (October 2021) . - pp 717 - 733[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 105-2021101 SL Revue Centre de documentation Revues en salle Disponible Linear regression and lines intersecting as a method of extracting punctual entities in a lidar point cloud / Marlo Antonio Ribeiro Martins in Boletim de Ciências Geodésicas, vol 27 n° 3 ([01/10/2021])
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Titre : Linear regression and lines intersecting as a method of extracting punctual entities in a lidar point cloud Type de document : Article/Communication Auteurs : Marlo Antonio Ribeiro Martins, Auteur ; Edson Aparecido Mitishita, Auteur Année de publication : 2021 Article en page(s) : 21 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] intersection spatiale
[Termes IGN] régression linéaire
[Termes IGN] semis de points
[Termes IGN] toitRésumé : (auteur) The characteristics of data points obtained by laser scanning (LiDAR) and images have been considered complementary in the field of photogrammetric applications, and research to improve their integrated use have recently intensified. This study aim to verify the performance of determining punctual entities in a LiDAR point cloud using linear regression and intersecting lines obtained from buildings with square rooftop containing four planes (hip roof), as well as compare punctual entities three-dimensional coordinates determined by planes intersection. Our results show that the proposed method was more accurate in determining three-dimensional coordinates than plan intersection method. The obtained coordinates were evaluated and framed into the map accuracy standard for digital cartographic products (PEC-PCD), besides being analyzed for trend and precision. Accuracy analysis results frame punctual entities three-dimensional coordinates into the 1:2,000 or lower scale for Class A of PEC-PCD. Numéro de notice : A2021-959 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1590/s1982-21702021000300022 En ligne : https://doi.org/10.1590/s1982-21702021000300022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100074
in Boletim de Ciências Geodésicas > vol 27 n° 3 [01/10/2021] . - 21 p.[article]Non-tidal loading of the Baltic Sea in Latvian GNSS time series / Diana Haritonova in Journal of applied geodesy, vol 15 n° 4 (October 2021)
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Titre : Non-tidal loading of the Baltic Sea in Latvian GNSS time series Type de document : Article/Communication Auteurs : Diana Haritonova, Auteur Année de publication : 2021 Article en page(s) : pp 293 - 304 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] Baltique, mer
[Termes IGN] coefficient de corrélation
[Termes IGN] Continuously Operating Reference Station network
[Termes IGN] données GNSS
[Termes IGN] effet de charge
[Termes IGN] Lettonie
[Termes IGN] marégraphe
[Termes IGN] niveau de la mer
[Termes IGN] série temporelle
[Termes IGN] station de référence
[Termes IGN] surcharge océaniqueRésumé : (auteur) The objective of this study is to investigate the effect of the Baltic Sea non-tidal loading in the territory of Latvia using observations of the GNSS continuously operating reference stations (CORS) of LatPos, EUPOS®-Riga, EPN and EstPos networks. The GNSS station daily coordinate time series obtained in a double-difference (DD) mode were used. For representation of the sea level dynamics, the Latvian tide gauge records were used. Performed correlation analysis is based on yearly data sets of these observations for the period from 2012 up to 2020. The approach discloses how the non-tidal loading can induce variations in the time series of the regional GNSS station network. This paper increases understanding of the Earth’s surface displacements occurring due to the non-tidal loading effect in Latvia, and is intended to raise the importance and necessity of improved Latvian GNSS time series by removing loading effects. Numéro de notice : A2021-750 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1515/jag-2021-0024 Date de publication en ligne : 23/06/2021 En ligne : https://doi.org/10.1515/jag-2021-0024 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98719
in Journal of applied geodesy > vol 15 n° 4 (October 2021) . - pp 293 - 304[article]On determination of the geoid from measured gradients of the Earth's gravity field potential / Pavel Novák in Earth-Science Reviews, vol 221 (October 2021)
PermalinkOn the TEC bias of altimeter satellites / Francisco Azpilicueta in Journal of geodesy, vol 95 n° 10 (October 2021)
PermalinkPerformance investigation of LAMBDA and bootstrapping methods for PPP narrow-lane ambiguity resolution / Omer Faruk Atiz in Geo-spatial Information Science, vol 24 n° 4 (October 2021)
PermalinkPhase unmixing of TerraSAR-X staring spotlight interferograms in building scale for PS height and deformation / Peng Liu in ISPRS Journal of photogrammetry and remote sensing, vol 180 (October 2021)
PermalinkPredicting total electron content in ionosphere using vector autoregression model during geomagnetic storm / Sumitra Iyer in Journal of applied geodesy, vol 15 n° 4 (October 2021)
PermalinkSpatial biodiversity modeling using high-performance computing cluster: A case study to access biological richness in Indian landscape / Hariom Singh in Geocarto international, vol 36 n° 18 ([01/10/2021])
PermalinkSpatial interpolation of mobile positioning data for population statistics / Anto Aasa in Journal of location-based services, vol 15 n° 4 ([01/10/2021])
PermalinkSpatial structure system of land use along urban rail transit based on GIS spatial clustering / Yu Gao in European journal of remote sensing, vol 54 sup 2 (2021)
PermalinkUnsupervised self-adaptive deep learning classification network based on the optic nerve microsaccade mechanism for unmanned aerial vehicle remote sensing image classification / Ming Cong in Geocarto international, vol 36 n° 18 ([01/10/2021])
PermalinkUrban geospatial information acquisition mobile mapping system based on close-range photogrammetry and IGS site calibration / Ming Guo in Geo-spatial Information Science, vol 24 n° 4 (October 2021)
PermalinkAssessment and prediction of urban growth for a mega-city using CA-Markov model / Veerendra Yadav in Geocarto international, vol 36 n° 17 ([15/09/2021])
PermalinkRecurrent-based regression of Sentinel time series for continuous vegetation monitoring / Anatol Garioud in Remote sensing of environment, vol 263 (15 September 2021)
Permalink3D map creation using crowdsourced GNSS data / Terence Lines in Computers, Environment and Urban Systems, vol 89 (September 2021)
PermalinkAccuracy estimation of site coordinates derived from GNSS-observations by non-classical error theory of measurements / Petro Dvulit in Geodesy and Geodynamics, vol 12 n° 5 (September 2021)
PermalinkAutomatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)
PermalinkBenford’s law and geographical information – the example of OpenStreetMap / Franz-Benjamin Mocnik in International journal of geographical information science IJGIS, vol 35 n° 9 (September 2021)
PermalinkClassification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)
PermalinkA constrained extended Kalman filter based on LS-VCE formulated by condition equations with prediction of cross-covariances / Vahid Mahboub in Survey review, Vol 53 n° 380 (September 2021)
PermalinkDetection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds / Alwin A. Hardenbol in Silva fennica, vol 55 n° 4 (September 2021)
PermalinkDouble adaptive intensity-threshold method for uneven Lidar data to extract road markings / Chengming Ye in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)
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