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Generation of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data / Behnaz Bigdeli in Survey review, vol 52 n° 371 (March 2020)
[article]
Titre : Generation of digital terrain model for forest areas using a new particle swarm optimization on LiDAR data Type de document : Article/Communication Auteurs : Behnaz Bigdeli, Auteur ; Masoomeh Gomroki, Auteur ; Parham Pahlavani, Auteur Année de publication : 2020 Article en page(s) : pp 115 - 125 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie
[Termes IGN] données lidar
[Termes IGN] erreur moyenne quadratique
[Termes IGN] filtrage de la végétation
[Termes IGN] interpolation polynomiale
[Termes IGN] Iran
[Termes IGN] modèle numérique de terrain
[Termes IGN] optimisation par essaim de particules
[Termes IGN] semis de points
[Termes IGN] surface forestièreRésumé : (auteur) Since Light Detection and Ranging (LiDAR) data are capable of distinguishing vegetation from bare earth, these data are used nowadays to produce digital terrain models (DTMs) for forest regions. In this research, raw LiDAR data were filtered using hybrid and slope-based filtering methods and the filtered data were then interpolated using the new modified particle swarm optimisation (PSO) and accordingly the results were compared with those achieved by the other intelligent and conventional interpolation methods. The new modified PSO optimized the polynomial degree for interpolation and found suitable parameters for optimisation. Two data sets from two forest regions in some northern regions of Iran located in Golestan province were selected to compare these methods. Region 1 with dense vegetation and region 2 with grass vegetation. The results indicated that the hybrid filter performed lower RMSE than the slope-based filter. Finally, the DTM with lowest RMSE was obtained using the hybrid filter and the modified PSO interpolation method with RMSE of 6 mm for region 1 (Tavar-kuh) and 61 mm for region 2 (Shastkola River Basin). Numéro de notice : A2020-078 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/00396265.2018.1530331 Date de publication en ligne : 10/10/2018 En ligne : https://doi.org/10.1080/00396265.2018.1530331 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94640
in Survey review > vol 52 n° 371 (March 2020) . - pp 115 - 125[article]An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data / Xiaogang Guo in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)
[article]
Titre : An OD flow clustering method based on vector constraints: a case study for Beijing taxi origin-destination data Type de document : Article/Communication Auteurs : Xiaogang Guo, Auteur ; Zhijie Xu, Auteur ; Jianqin Zhang, Auteur Année de publication : 2020 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] classification par nuées dynamiques
[Termes IGN] distance euclidienne
[Termes IGN] données de flux
[Termes IGN] données vectorielles
[Termes IGN] erreur moyenne quadratique
[Termes IGN] origine - destination
[Termes IGN] Pékin (Chine)
[Termes IGN] regroupement de données
[Termes IGN] taxi
[Termes IGN] trafic routier
[Termes IGN] zone urbaineRésumé : (auteur) Origin-destination (OD) flow pattern mining is an important research method of urban dynamics, in which OD flow clustering analysis discovers the activity patterns of urban residents and mine the coupling relationship of urban subspace and dynamic causes. The existing flow clustering methods are limited by the spatial constraints of OD points, rely on the spatial similarity of geographical points, and lack in-depth analysis of high-dimensional flow characteristics, and therefore it is difficult to find irregular flow clusters. In this paper, we propose an OD flow clustering method based on vector constraints (ODFCVC), which defines OD flow event point and OD flow vector to express the spatial location relationship and geometric flow behavior characteristics of OD flow. First, the OD flow vector coordinate system is normalized by the Euclidean distance-based OD flow event point spatial clustering, and then the OD flow clusters with similar flow patterns are mined using adjusted cosine similarity-based OD flow vector feature clustering. The transformation of OD data from point set space to vector space is realized by constraining the vector coordinate system and vector similarity through two-step clustering, which simplifies the calculation of high-dimensional similarity of OD flow and helps mining representative OD flow clusters in flow space. Due to the OD flow cluster property, the k-means algorithm is selected as the basic clustering logic in the two-step clustering method, and a sum of squared error perceptually important points algorithm considering silhouette coefficients (SSEPIP) is adopted to automatically extract the optimal cluster number without defining any parameters. Tested by origin-destination flow data in Beijing, China, new traffic flow communities based on traffic hubs are obtained by using the ODFCVC method, and irregular traffic flow clusters (including cluster mode, divergence mode, and convergence mode) with representative travel trends are found. Numéro de notice : A2020-114 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9020128 Date de publication en ligne : 22/02/2020 En ligne : https://doi.org/10.3390/ijgi9020128 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94720
in ISPRS International journal of geo-information > vol 9 n° 2 (February 2020)[article]Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture / Ju Hyoung Lee in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)
[article]
Titre : Using Ranked Probability Skill Score (RPSS) as Nonlocal Root-Mean-Square Errors (RMSEs) for Mitigating Wet Bias of Soil Moisture Ocean Salinity (SMOS) Soil Moisture Type de document : Article/Communication Auteurs : Ju Hyoung Lee, Auteur Année de publication : 2020 Article en page(s) : pp 91 - 98 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Afrique occidentale
[Termes IGN] données multitemporelles
[Termes IGN] erreur moyenne quadratique
[Termes IGN] erreur systématique
[Termes IGN] humidité du sol
[Termes IGN] image SMOS
[Termes IGN] salinitéRésumé : (Auteur) To mitigate instantaneously evolving biases in satellite retrievals, a stochastic approach is applied over West Africa. This stochastic approach independently self-corrects Soil Moisture Ocean Salinity (SMOS) wet biases, unlike the cumulative density function (CDF) matching that rescales satellite retrievals with respect to several years of reference data. Ranked probability skill score (RPSS) is used as nonlocal root-mean-square errors (RMSEs) to assess stochastic retrievals. Stochastic method successfully decreases RMSEs from 0.146 m3/m3 to 0.056 m3/m3 in the Republic of Benin and from 0.080 m3/m3 to 0.038 m3/m3 in Niger, while the CDF matching method exacerbates the original SMOS biases up to 0.141 m3/m3 in Niger, and 0.120 m3/m3 in Benin. Unlike the CDF matching or European Centre for Medium-Range Weather Forecasts (ECMWF) Re-Analysis (ERA))–interim soil moisture, only a stochastic retrieval responds to Tropical Rainfall Measuring Mission rainfall. Based on the effects of bias correction, RPSS is suggested as a nonlocal verification without needing local measurements. Numéro de notice : A2020-126 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.2.91 Date de publication en ligne : 01/02/2020 En ligne : https://doi.org/10.14358/PERS.86.2.91 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94772
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 2 (February 2020) . - pp 91 - 98[article]Modelling the orthoimage accuracy using DEM accuracy and off-nadir angle / Altan Yilmaz in Geocarto international, Vol 35 n° 1 ([02/01/2020])
[article]
Titre : Modelling the orthoimage accuracy using DEM accuracy and off-nadir angle Type de document : Article/Communication Auteurs : Altan Yilmaz, Auteur ; Mustafa Erdogan, Auteur Année de publication : 2020 Article en page(s) : pp 1 - 16 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] angle nadiral
[Termes IGN] centrale inertielle
[Termes IGN] erreur
[Termes IGN] erreur moyenne quadratique
[Termes IGN] modèle empirique
[Termes IGN] modèle numérique de surface
[Termes IGN] orthoimage
[Termes IGN] planimétrie
[Termes IGN] point d'appuiRésumé : (auteur) Orthoimages are differentially rectified images that are corrected for the distortions caused especially by image tilt and topographic relief. The orientation, digital elevation model (DEM) and off-nadir angle plays an important role in orthoimage accuracy. The orientation error mostly occurs due to the quality and distribution of the ground control points. In this study, an attempt has been made to model the remaining errors by keeping the orientation error constant. To model the accuracy, orthoimages are produced with eight DEMs having different accuracies and are assessed using 50 check points. As the theoretical model cannot reflect the real world exactly, an empirical model is used for estimating the orthoimage accuracy. This proposed model was validated by another dataset. It is concluded that statistically there is no significant difference between the calculated model and real planimetric errors. The proposed model can be used in predicting orthoimage accuracy provided that the DEM accuracy and off-nadir angles of the points are known. Numéro de notice : A2020-016 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1493157 Date de publication en ligne : 12/09/2018 En ligne : https://doi.org/10.1080/10106049.2018.1493157 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94409
in Geocarto international > Vol 35 n° 1 [02/01/2020] . - pp 1 - 16[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 059-2020011 RAB Livre Centre de documentation En réserve L003 Disponible A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor / Liangke Huang in Journal of geodesy, vol 93 n° 2 (February 2019)
[article]
Titre : A new global grid model for the determination of atmospheric weighted mean temperature in GPS precipitable water vapor Type de document : Article/Communication Auteurs : Liangke Huang, Auteur ; Weiping Jiang, Auteur ; Lilong Liu, Auteur ; Hua Chen, Auteur ; Shirong Ye, Auteur Année de publication : 2019 Article en page(s) : pp 159 - 176 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] coordonnées GPS
[Termes IGN] données météorologiques
[Termes IGN] erreur moyenne quadratique
[Termes IGN] Global Geodetic Observing System
[Termes IGN] modèle de géopotentiel
[Termes IGN] prévision météorologique
[Termes IGN] radiosondage
[Termes IGN] régression linéaire
[Termes IGN] retard troposphérique zénithal
[Termes IGN] vapeur d'eauRésumé : (auteur) In ground-based global positioning system (GPS) meteorology, atmospheric weighted mean temperature, Tm, plays a very important role in the progress of retrieving precipitable water vapor (PWV) from the zenith wet delay of the GPS. Generally, most of the existing Tm models only take either latitude or altitude into account in modeling. However, a great number of studies have shown that Tm is highly correlated with both latitude and altitude. In this study, a new global grid empirical Tm model, named as GGTm, was established by a sliding window algorithm using global gridded Tm data over an 8-year period from 2007 to 2014 provided by TU Vienna, where both latitude and altitude variations are considered in modeling. And the performance of GGTm was assessed by comparing with the Bevis formula and the GPT2w model, where the high-precision global gridded Tm data as provided by TU Vienna and the radiosonde data from 2015 are used as reference values. The results show the significant performance of the new GGTm model against other models when compared with gridded Tm data and radiosonde data, especially in the areas with great undulating terrain. Additionally, GGTm has the global mean RMSPWV and RMSPWV/PWV values of 0.26 mm and 1.28%, respectively. The GGTm model, fed only by the day of the year and the station coordinates, could provide a reliable and accurate Tm value, which shows the possible potential application in real-time GPS meteorology, especially for the application of low-latitude areas and western China. Numéro de notice : A2019-077 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1148-9 Date de publication en ligne : 15/05/2018 En ligne : https://doi.org/10.1007/s00190-018-1148-9 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92191
in Journal of geodesy > vol 93 n° 2 (February 2019) . - pp 159 - 176[article]Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations / Kun Liu in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkSuper-resolution of Sentinel-2 images : Learning a globally applicable deep neural network / Charis Lanaras in ISPRS Journal of photogrammetry and remote sensing, vol 146 (December 2018)PermalinkLa mesure du niveau de la mer par bouées GPS : l'expérience multi-capteurs de l'île d'Aix / Gaël André in XYZ, n° 140 (septembre - novembre 2014)PermalinkRoot mean square error compared to, and contrasted with, standard deviation / Thomas H. Meyer in SaLIS Surveying and land information science, vol 72 n° 3 (September 2012)PermalinkGeneralization of DEM for terrain analysis using a compound method / Q. Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)PermalinkOrthorectification of VHR optical satellite data exploiting the geometric accuracy of TerraSAR-X data / Peter Reinartz in ISPRS Journal of photogrammetry and remote sensing, vol 66 n° 1 (January - February 2011)PermalinkVertical accuracy of digital elevation model from Shuttle Radar Topographic Mission: a case study / Ashu Sharma in Geocarto international, vol 25 n° 4 (July 2010)PermalinkConsistency of accuracy assessment indices for soft classification: simulation analysis / J. Chen in ISPRS Journal of photogrammetry and remote sensing, vol 65 n° 2 (March - April 2010)PermalinkFormulation of distortion error for the line-of-sight (LOS) vector adjustment model and its role in restitution of SPOT imagery / Hyung-Sup Jung in ISPRS Journal of photogrammetry and remote sensing, vol 63 n° 6 (November - December 2008)PermalinkCapture de layers durant une session dans un globe virtuel / G. Mazabraud (2008)Permalink