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Automatic canola mapping using time series of Sentinel 2 images / Davoud Ashourloo in ISPRS Journal of photogrammetry and remote sensing, vol 156 (October 2019)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 156 (October 2019) . - pp 63 - 76 Titre : Automatic canola mapping using time series of Sentinel 2 images Type de document : Article/Communication Auteurs : Davoud Ashourloo, Auteur ; Hamid Salehi Shahrabi, Auteur ; Mohsen Azadbakht, Auteur ; Hossein Aghighi, Auteur ; Hamed Nematollahi, Auteur ; Abbas Alimohammadi, Auteur ; Ali Akbar Matkan, Auteur Année de publication : 2019 Article en page(s) : pp 63 - 76 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] agriculture de précision [Termes descripteurs IGN] Brassica napus subsp. napus [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] image RVB [Termes descripteurs IGN] image Sentinel-MSI [Termes descripteurs IGN] Iran [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] Oklahoma (Etats-Unis) [Termes descripteurs IGN] rendement agricole [Termes descripteurs IGN] série temporelle Résumé : (Auteur) Different techniques utilized for mapping various crops are mainly based on using training dataset. But, due to difficulties of access to a well-represented training data, development of automatic methods for detection of crops is an important need which has not been considered as it deserves. Therefore, main objective of present study was to propose a new automatic method for canola (Brassica napus L.) mapping based on Sentinel 2 satellite time series data. Time series data of three study sites in Iran (Moghan, Gorgan, Qazvin) and one site in USA: (Oklahoma), were used. Then, spectral reflectance values of canola in various spectral bands were compared with those of the other crops during the growing season. NDVI, Red and Green spectral bands were successfully applied for automatic identification of canola flowering date using the threshold values. Examination of the fisher function indicated that multiplication of the near-infrared (NIR) band by the sum of red and green bands during the flowering date is an efficient index to differentiate canola from the other crops. The Kappa and overall accuracy (OA) for the four study sites were more than 0.75 and 88%, respectively. Results of this research demonstrated the potential of the proposed approach for canola mapping using time series of remotely sensed data. Numéro de notice : A2019-317 Thématique : FORET/IMAGERIE Nature : Article DOI : 10.1016/j.isprsjprs.2019.08.007 date de publication en ligne : 09/08/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.08.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93355 [article]

Introducing a vertical land motion model for improving estimates of sea level rates derived from tide gauge records affected by earthquakes / Anna Klos in GPS solutions, vol 23 n° 4 (October 2019)  

Public [article]  inGPS solutions > vol 23 n° 4 (October 2019) Titre : Introducing a vertical land motion model for improving estimates of sea level rates derived from tide gauge records affected by earthquakes Type de document : Article/Communication Auteurs : Anna Klos, Auteur ; Jürgen Kusche, Auteur ; L. Fenoglio-Marc, Auteur ; et al., Auteur Année de publication : 2019 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes descripteurs IGN] changement du niveau de la mer [Termes descripteurs IGN] déformation verticale de la croute terrestre [Termes descripteurs IGN] données marégraphiques [Termes descripteurs IGN] marée océanique [Termes descripteurs IGN] modèle de simulation [Termes descripteurs IGN] niveau de la mer [Termes descripteurs IGN] Pacifique (océan) [Termes descripteurs IGN] positionnement par GPS [Termes descripteurs IGN] séisme [Termes descripteurs IGN] série temporelle Résumé : (Auteur) We reassess the absolute and relative sea level changes at 38 tide gauge stations in the earthquake-affected Western North Pacific for the 1993–2015 period, focusing on the vertical land motion (VLM) which is crucial for narrowing the gap between these estimates. In this area, simply discarding all earthquake-affected sites, one overestimates the average regional sea level rise by more than 0.5 mm/year. Disregarding VLM would lead to misestimating local sea level trends between 0.2 and 7.6 mm/year. If accounted for, but modeled as linear during the entire time span, VLM leads to regional absolute sea level rise errors of up to 0.4 mm/year. Therefore, we introduce a new methodology that better represents the Global Positioning System (GPS)-derived nonlinear VLM by accounting for co-seismic offsets, changes in the vertical velocities and post-seismic transient. Also, for the first time, a combination of white and power-law noises is added to this nonlinear model to derive proper uncertainties of VLM. We find a maximum difference of 15.3 mm/year between pre- and post-seismic vertical velocities. The GPS-sensed vertical co-seismic displacement approaches 36 mm. Assuming the changes in vertical velocities and displacement due to the tectonic movements is not accounted for, and then, estimating absolute sea level rise from tide gauges can result in an error of 10 mm/year. Introducing a new nonlinear VLM model improves absolute tide gauge sea level estimates by 20% on average. Finally, for the reconstructed Western North Pacific sea level, altimetry agrees best with tide gauge data corrected employing the new nonlinear VLM model. Numéro de notice : A2019-333 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s10291-019-0896-1 date de publication en ligne : 24/07/2019 En ligne : https://doi.org/10.1007/s10291-019-0896-1 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93422 [article]

A novel method for separating woody and herbaceous time series / Qiang Zhou in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 7 (July 2019)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 85 n° 7 (July 2019) . - pp 509 - 520 Titre : A novel method for separating woody and herbaceous time series Type de document : Article/Communication Auteurs : Qiang Zhou, Auteur ; Shuguang Liu, Auteur ; Michael J Hill, Auteur Année de publication : 2019 Article en page(s) : pp 509 - 520 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] Afrique australe [Termes descripteurs IGN] bois [Termes descripteurs IGN] extraction de la végétation [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image Ikonos [Termes descripteurs IGN] image Landsat-SWIR [Termes descripteurs IGN] image Terra-MODIS [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] plante herbacée [Termes descripteurs IGN] savane [Termes descripteurs IGN] série temporelle [Termes descripteurs IGN] variation saisonnière Résumé : (auteur) Mapping the spatial distribution of woody and herbaceous vegetation in high temporal resolution in savannas would be beneficial for modeling interrelationships between trees and grasses, and monitoring fuel loads and biomass for livestock. In this study, we developed a frequency decomposition method to separate woody and herbaceous vegetation components using Normalized Difference Vegetation Index (NDVI) time series. The results were validated using fractional cover data derived from high-resolution images. The validation revealed a close relationship between our decomposed NDVI and corresponding fractional cover (R2 = 0.55 and 0.64 for woody and herbaceous components, respectively). We examined the spatial and temporal patterns of the decomposed NDVI, where woody and herbaceous NDVI showed different responses to precipitation. The methods proposed in this study can be used to separate the woody and herbaceous NDVI time series as an alternative approach for monitoring woody and herbaceous vegetation interrelationships related to climatic drivers. Numéro de notice : A2019-259 Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.85.7.509 date de publication en ligne : 01/07/2019 En ligne : https://doi.org/10.14358/PERS.85.7.509 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93062 [article]

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PPP-RTK based on undifferenced and uncombined observations: theoretical and practical aspects / Baocheng Zhang in Journal of geodesy, vol 93 n°7 (July 2019)  

Public [article]  inJournal of geodesy > vol 93 n°7 (July 2019) . - pp 1011 - 1024 Titre : PPP-RTK based on undifferenced and uncombined observations: theoretical and practical aspects Type de document : Article/Communication Auteurs : Baocheng Zhang, Auteur ; Yongchang Chen, Auteur ; Yunbin Yuan, Auteur Année de publication : 2019 Article en page(s) : pp 1011 - 1024 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes descripteurs IGN] ambiguïté entière [Termes descripteurs IGN] données GNSS [Termes descripteurs IGN] mesurage de phase [Termes descripteurs IGN] positionnement cinématique en temps réel [Termes descripteurs IGN] positionnement par GNSS [Termes descripteurs IGN] positionnement ponctuel précis [Termes descripteurs IGN] série temporelle Résumé : (auteur) A synthesis of two prevailing global navigation satellite system positioning technologies, namely the precise point positioning and the network-based real-time kinematic, results in the emergence of the PPP-RTK, enabling single-receiver users to achieve high positioning accuracy with reasonable timeliness through integer ambiguity resolution. The realization of PPP-RTK needs to accomplish two sequential tasks. The first task is to determine a class of corrections including, among others, the satellite phase biases (SPBs) at the network level. With these corrections, the second task, then, is to solve for the ambiguity-fixed, absolute position at the user level. In this contribution, we revisit three variants (geometry-free, geometry-fixed and geometry-plus-satellite-clock-fixed) of the undifferenced and uncombined PPP-RTK network model and then point out their implications for practical use. We also carry out a case study using multi-day, dual-frequency global positioning system data from the crustal movement observation network of China stations, aiming to figure out what are the most appropriate linear combinations of the SPBs to be transmitted to the users from the viewpoint of decorrelation, and to assess the static and kinematic positioning performance. Numéro de notice : A2019-357 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1220-5 date de publication en ligne : 06/12/2018 En ligne : https://doi.org/10.1007/s00190-018-1220-5 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93425 [article]

Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach / Jian Zhao in Marine geodesy, vol 42 n° 4 (July 2019)  

Public [article]  inMarine geodesy > vol 42 n° 4 (July 2019) . - pp 344 - 366 Titre : Sea level prediction in the Yellow Sea from satellite altimetry with a combined least squares-neural network approach Type de document : Article/Communication Auteurs : Jian Zhao, Auteur ; Yanguo Fan, Auteur ; Yuxiang Mu, Auteur Année de publication : 2019 Article en page(s) : pp 344 - 366 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie physique [Termes descripteurs IGN] changement du niveau de la mer [Termes descripteurs IGN] détection d'anomalie [Termes descripteurs IGN] données altimétriques [Termes descripteurs IGN] données Jason [Termes descripteurs IGN] données Topex-Poseidon [Termes descripteurs IGN] image ERS-SAR [Termes descripteurs IGN] méthode des moindres carrés [Termes descripteurs IGN] Pacifique nord [Termes descripteurs IGN] prévision [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] série temporelle Résumé : (auteur) Accessible high-quality observation datasets and proper modeling process are critically required to accurately predict sea level rise in coastal areas. This study focuses on developing and validating a combined least squares-neural network approach applicable to the short-term prediction of sea level variations in the Yellow Sea, where the periodic terms and linear trend of sea level change are fitted and extrapolated using the least squares model, while the prediction of the residual terms is performed by several different types of artificial neural networks. The input and output data used are the sea level anomalies (SLA) time series in the Yellow Sea from 1993 to 2016 derived from ERS-1/2, Topex/Poseidon, Jason-1/2, and Envisat satellite altimetry missions. Tests of different neural network architectures and learning algorithms are performed to assess their applicability for predicting the residuals of SLA time series. Different neural networks satisfactorily provide reliable results and the root mean square errors of the predictions from the proposed combined approach are less than 2 cm and correlation coefficients between the observed and predicted SLA are up to 0.87. Results prove the reliability of the combined least squares-neural network approach on the short-term prediction of sea level variability close to the coast. Numéro de notice : A2019-281 Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2019.1626306 date de publication en ligne : 12/06/2019 En ligne : https://doi.org/10.1080/01490419.2019.1626306 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93115 [article]

A breakpoint detection in the mean model with heterogeneous variance on fixed time-intervals / Olivier Bock in Statistics and Computing, vol 29 Online First (May 2019)  

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Journées de la recherche 2019 / Anonyme in Géomatique expert, n° 127 (avril - mai 2019)

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Analysis of ocean tide loading displacements by GPS kinematic precise point positioning: a case study at the China coastal site SHAO / H. Zhao in Survey review, vol 51 n° 365 (March 2019)  

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A comparative study between least square and total least square methods for time-series analysis and quality control of sea level observations / Mahmoud Pirooznia in Marine geodesy, vol 42 n° 2 (March 2019)  

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DuPLO: A DUal view Point deep Learning architecture for time series classificatiOn / Roberto Interdonato in ISPRS Journal of photogrammetry and remote sensing, vol 149 (March 2019)  

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Temporal and spatial high-resolution climate data from 1961 to 2100 for the German National Forest Inventory (NFI) / Helge Dietrich in Annals of Forest Science [en ligne], vol 76 n° 1 (March 2019)  

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Combined orbits and clocks from IGS second reprocessing / Jake Griffiths in Journal of geodesy, vol 93 n° 2 (February 2019)  

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Assessment of different vegetation parameters for parameterizing the coupled water cloud model and advanced integral equation model for soil moisture retrieval using time series Sentinel-1A data / Long Wang in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 1 (January 2019)  

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DataPink, l'IA au service de l'information géographique / Anonyme in Géomatique expert, n° 126 (janvier - février 2019)

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DPOD2014 : A new DORIS extension of ITRF2014 for precise orbit determination / Guilhem Moreaux in Advances in space research, vol 63 n° 1 (1 January 2019)  

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