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Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities / Clément Benoist in Journal of geodynamics, vol 135 (April 2020)
[article]
Titre : Accounting for spatiotemporal correlations of GNSS coordinate time series to estimate station velocities Type de document : Article/Communication Auteurs : Clément Benoist , Auteur ; Xavier Collilieux , Auteur ; Paul Rebischung , Auteur ; Zuheir Altamimi , Auteur ; Olivier Jamet , Auteur ; Laurent Métivier , Auteur ; Kristel Chanard , Auteur ; Liliane Bel, Auteur Année de publication : 2020 Projets : GEODESIE / Coulot, David, Université de Paris / Clerici, Christine Article en page(s) : n° 101693 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux
[Termes IGN] corrélation
[Termes IGN] covariance
[Termes IGN] données spatiotemporelles
[Termes IGN] repère de référence terrestre conventionnel
[Termes IGN] série temporelle
[Termes IGN] vitesseRésumé : (auteur) It is well known that GNSS permanent station coordinate time series exhibit time-correlated noise. Spatial correlations between coordinate time series of nearby stations are also long-established and generally handled by means of spatial filtering techniques. Accounting for both the temporal and spatial correlations of the noise via a spatiotemporal covariance model is however not yet a common practice. We demonstrate in this paper the interest of using such a spatiotemporal covariance model of the stochastic variations in GNSS time series in order to estimate long-term station coordinates and especially velocities.
We provide a methodology to rigorously assess the covariances between horizontal coordinate variations and use it to derive a simple exponential spatiotemporal covariance model for the stochastic variations in the IGS repro2 station coordinate time series. We then use this model to estimate station velocities for two selected datasets of 10 time series in Europe and 11 time series in the USA. We show that coordinate prediction as well as velocity determination from short time series are improved when using this spatiotemporal model, as compared with the case where spatiotemporal correlations are ignored.Numéro de notice : A2020-460 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.jog.2020.101693 Date de publication en ligne : 13/01/2020 En ligne : https://doi.org/10.1016/j.jog.2020.101693 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95385
in Journal of geodynamics > vol 135 (April 2020) . - n° 101693[article]Experte image aérienne... / Laurent Polidori in Géomètre, n° 2179 (avril 2020)
[article]
Titre : Experte image aérienne... Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2020 Article en page(s) : pp 44 - 45 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] analyse comparative
[Termes IGN] données spatiotemporelles
[Termes IGN] photographie aérienneRésumé : (Auteur) L'avantage des photographies aériennes par rapport à de simples mesures est qu'au-delà des amplitudes de déplacements, elles permettent d'en comprendre la nature et ainsi d'éclairer pleinement l'expertise. Numéro de notice : A2020-179 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94847
in Géomètre > n° 2179 (avril 2020) . - pp 44 - 45[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 063-2020041 RAB Revue Centre de documentation En réserve L003 Disponible Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China / Mingyue Wang in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
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Titre : Spatiotemporal variation of NDVI in the vegetation growing season in the source region of the yellow river, China Type de document : Article/Communication Auteurs : Mingyue Wang, Auteur ; Jun’e Fu, Auteur ; Zhitao Wu, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] coefficient de corrélation
[Termes IGN] données météorologiques
[Termes IGN] données spatiotemporelles
[Termes IGN] écosystème
[Termes IGN] Fleuve jaune (Chine)
[Termes IGN] image Aqua-MODIS
[Termes IGN] image SPOT
[Termes IGN] image Terra-MODIS
[Termes IGN] modèle de simulation
[Termes IGN] modèle dynamique
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] précipitation
[Termes IGN] série temporelle
[Termes IGN] température
[Termes IGN] variation saisonnièreRésumé : (auteur) Research on vegetation variation is an important aspect of global warming studies. The quantification of the relationship between vegetation change and climate change has become a central topic and challenge in current global change studies. The source region of the Yellow River (SRYR) is an appropriate area to study global change because of its unique natural conditions and vulnerable terrestrial ecosystem. Therefore, we chose the SRYR for a case study to determine the driving forces behind vegetation variation under global warming. Using the Normalized Difference Vegetation Index (NDVI) and climate data, we investigated the NDVI variation in the growing season in the region from 1998 to 2016 and its response to climate change based on trend analysis, the Mann–Kendall trend test and partial correlation analysis. Finally, an NDVI–climate mathematical model was built to predict the NDVI trends from 2020 to 2038. The results indicated the following: (1) over the past 19 years, the NDVI showed an increasing trend, with a growth rate of 0.00204/a. There was an upward trend in NDVI over 71.40% of the region. (2) Both the precipitation and temperature in the growing season showed upward trends over the last 19 years. NDVI was positively correlated with precipitation and temperature. The areas with significant relationships with precipitation covered 31.01% of the region, while those with significant relationships with temperature covered 56.40%. The sensitivity of the NDVI to temperature was higher than that to precipitation. Over half (56.58%) of the areas were found to exhibit negative impacts of human activities on the NDVI. (3) According to the simulation, the NDVI will increase slightly over the next 19 years, with a linear tendency of 0.00096/a. From the perspective of spatiotemporal changes, we combined the past and future variations in vegetation, which could adequately reflect the long-term vegetation trends. The results provide a theoretical basis and reference for the sustainable development of the natural environment and a response to vegetation change under the background of climate change in the study area. Numéro de notice : A2020-262 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040282 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040282 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95022
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 17 p.[article]Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network / Adil Alim in Geoinformatica, vol 24 n° 2 (April 2020)
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Titre : Techniques for efficient detection of rapid weather changes and analysis of their impacts on a highway network Type de document : Article/Communication Auteurs : Adil Alim, Auteur ; Aparna Joshi, Auteur ; Feng Chen, Auteur ; Catherine T. Lawson, Auteur Année de publication : 2020 Article en page(s) : pp 269 – 299 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] corrélation
[Termes IGN] détection d'événement
[Termes IGN] détection de changement
[Termes IGN] données spatiotemporelles
[Termes IGN] entretien du réseau
[Termes IGN] hiver
[Termes IGN] météorologie
[Termes IGN] prévision météorologique
[Termes IGN] réseau routier
[Termes IGN] sécurité routière
[Termes IGN] trafic routierRésumé : (auteur) Adverse weather conditions have a significant impact on the safety, mobility, and efficiency of highway networks. Weather contributed to 23 percent of all non-reoccurring delay and approximately 544 million vehicle hours of delay each year (2014). Nearly 2.3 billion dollars each year are spent by transportation agencies for winter maintenance that contribute to close to 20 percent of most DOT’s yearly budgets (2014). These safety and mobility factors make it important to develop new and more effective methods to address road conditions during adverse weather conditions. Given weather and traffic sensors installed along side of the highway networks, how can we automatically detect weather and traffic change events and prevent from the traffic delay or harsh weather accidents? To this end, we propose a novel framework to address this problem. This paper develops techniques for efficiently detecting rapid weather change events and analyzing their impacts on the traffic flow characteristics of a highway network. It is composed of three components, including 1) detection of rapid weather change events in a highway network using the streaming weather information from a sensor network of weather stations; 2) detection of rapid traffic change events on the traffic flow characteristics (e.g., travel time) of the highway network; and 3) analysis of correlations between the detected weather and traffic change events in space and time. The proposed approach was applied to a weather dataset provided by New York State Mesonet and a traffic flow dataset the National Performance Management Research Data Set (NPMRDS) provided by NYSDOT. The empirical results provide potential evidence about the significant impacts of rapid weather change events on traffic flow characteristics of the Interstate 90 (I-90) Highway in the state of New York. We show the quantitative performance evaluation of our change event detection algorithm and three baseline methods on manually labeled the weather dataset and our method outperforms baselines in terms of precision, recall and F-score. We present the analysis of Top K detected change events as case studies and also provide the spatio-temporal correlation statistics of top k weather and traffic change events. The limitations of the proposed approach and the empirical study are also discussed. Numéro de notice : A2020-358 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10707-020-00395-x Date de publication en ligne : 12/02/2020 En ligne : https://doi.org/10.1007/s10707-020-00395-x Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95263
in Geoinformatica > vol 24 n° 2 (April 2020) . - pp 269 – 299[article]A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety / Mayra Salcedo-Gonzalez in ISPRS International journal of geo-information, vol 9 n° 3 (March 2020)
[article]
Titre : A novel method of spatiotemporal dynamic geo-visualization of criminal data, applied to command and control centers for public safety Type de document : Article/Communication Auteurs : Mayra Salcedo-Gonzalez, Auteur ; Julio Suarez-Paez, Auteur ; Manuel Esteve, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : 17 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] cartographie des risques
[Termes IGN] Colombie
[Termes IGN] criminalité
[Termes IGN] données spatiotemporelles
[Termes IGN] géoréférencement
[Termes IGN] géovisualisation
[Termes IGN] gestion des ressources humaines
[Termes IGN] gestion urbaine
[Termes IGN] logiciel libre
[Termes IGN] protection civile
[Termes IGN] risque social
[Termes IGN] système d'information urbain
[Termes IGN] système de contrôle
[Termes IGN] ville intelligenteRésumé : (auteur) This article shows a novel geo-visualization method of dynamic spatiotemporal data that allows mobility and concentration of criminal activity to be study. The method was developed using, only and significantly, real data of Santiago de Cali (Colombia), collected by the Colombian National Police (PONAL). This method constitutes a tool that allows criminal influx to be analyzed by concentration, zone, time slot and date. In addition to the field experience of police commanders, it allows patterns of criminal activity to be detected, thereby enabling a better distribution and management of police resources allocated to crime deterrence, prevention and control. Additionally, it may be applied to the concepts of safe city and smart city of the PONAL within the architecture of Command and Control System (C2S) of Command and Control Centers for Public Safety. Furthermore, it contributes to a better situational awareness and improves the future projection, agility, efficiency and decision-making processes of police officers, which are all essential for fulfillment of police missions against crime. Finally, this was developed using an open source software, it can be adapted to any other city, be used with real-time data and be implemented, if necessary, with the geographic software of any other C2S. Numéro de notice : A2020-259 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.3390/ijgi9030160 Date de publication en ligne : 10/03/2020 En ligne : https://doi.org/10.3390/ijgi9030160 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95016
in ISPRS International journal of geo-information > vol 9 n° 3 (March 2020) . - 17 p.[article]Spectral–spatial–temporal MAP-based sub-pixel mapping for land-cover change detection / Da He in IEEE Transactions on geoscience and remote sensing, vol 58 n° 3 (March 2020)PermalinkThermal unmixing based downscaling for fine resolution diurnal land surface temperature analysis / Jiong Wang in ISPRS Journal of photogrammetry and remote sensing, vol 161 (March 2020)PermalinkComplex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)PermalinkLandslide displacement mapping based on ALOS-2/PALSAR-2 data using image correlation techniques and SAR interferometry: application to the Hell-Bourg landslide (Salazie Circle, La Réunion Island) / Daniel Raucoules in Geocarto international, vol 35 n° 2 ([01/02/2020])PermalinkÉtude de la vapeur d’eau atmosphérique à partir de données GNSS dans le bassin sud-ouest de l’océan Indien et applications à l’étude du climat et des cyclones tropicaux / Edouard Lees (2020)PermalinkFusion entre bases de données hétérogènes concernant la pollution des sols [diaporama] / Chuanming Dong (2020)PermalinkGeographies of maritime transport, Ch. 4. Geography versus topology in the evolution of the global container shipping network (1977-2016) / César Ducruet (2020)PermalinkPermalinkUn modèle spatio-temporel hybride de SIG temporel : application à la géomorphologie marine / Younes Hamdani (2020)PermalinkA new cellular automata framework of urban growth modeling by incorporating statistical and heuristic methods / Yongjiu Feng in International journal of geographical information science IJGIS, vol 34 n° 1 (January 2020)Permalink