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A combined drought monitoring index based on multi-sensor remote sensing data and machine learning / Hongzhu Han in Geocarto international, vol 36 n° 10 ([01/06/2021])  

Public [article]  inGeocarto international > vol 36 n° 10 [01/06/2021] . - pp 1161-1177 Titre : A combined drought monitoring index based on multi-sensor remote sensing data and machine learning Type de document : Article/Communication Auteurs : Hongzhu Han, Auteur ; Jianjun Bai, Auteur ; Jianwu Yan, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 1161-1177 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] apprentissage automatique [Termes IGN] Chensi (Chine) [Termes IGN] classification par forêts aléatoires [Termes IGN] évapotranspiration [Termes IGN] humidité du sol [Termes IGN] image Terra-MODIS [Termes IGN] image TRMM-MI [Termes IGN] indice d'humidité [Termes IGN] indice de végétation [Termes IGN] précipitation [Termes IGN] sécheresse [Termes IGN] surveillance météorologique [Termes IGN] température au sol Résumé : (Auteur) The occurrence of drought is related to complicated interactions between many factors, such as precipitation, temperature, evapotranspiration and vegetation. In this study, the relationships between drought and precipitation, temperature, vegetation and evapotranspiration were investigated with a random forest (RF), and a new combined drought monitoring index (CDMI) was constructed. The effectiveness of the CDMI in monitoring drought in Shaanxi Province was verified by the in situ 1 ∼ 12-month standardized precipitation index (SPI); relative soil moisture (RSM) and four other commonly used remote sensing drought monitoring indices. The results show that CDMI is more correlated with the SPI and RSM than the four indices. Moreover, the spatial distributions of drought for the CDMI and RSM are similar. Therefore, the CDMI can be used to monitor droughts in Shaanxi Province, and machine learning can explore the relationships between various factors and establish a drought index without knowledge of the causal mechanisms of these factors. Numéro de notice : A2021-369 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2019.1633423 date de publication en ligne : 27/06/2019 En ligne : https://doi.org/10.1080/10106049.2019.1633423 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97734 [article]

Advanced GNSS tropospheric products for monitoring severe weather events and climate, ch. 5. Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3) / Olivier Bock (2020)  

Public contenu dans Advanced GNSS tropospheric products for monitoring severe weather events and climate / Jonathan Jones (2020)   Titre de série : Advanced GNSS tropospheric products for monitoring severe weather events and climate, ch. 5 Titre : Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3) Type de document : Chapitre/Contribution Auteurs : Olivier Bock , Auteur ; Rosa Pacione, Auteur ; F. Ahmed, Auteur ; A. Araszkiewicz, Auteur ; et al., Auteur ; Samuel Nahmani , Auteur ; Paul Rebischung , Auteur ; Pascal Willis , Auteur Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Projets : GNSS4SWEC / Importance : pp 267 - 402 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] données GNSS [Termes IGN] format SINEX [Termes IGN] propagation troposphérique [Termes IGN] retard troposphérique zénithal [Termes IGN] série temporelle [Termes IGN] surveillance météorologique [Termes IGN] teneur intégrée en vapeur d'eau Résumé : (Auteur) There has been growing interest in recent years in the use of homogeneously reprocessed ground-based GNSS, VLBI, and DORIS measurements for climate applications. Existing datasets are reviewed and the sensitivity of tropospheric estimates to the processing details is discussed. The uncertainty in the derived IWV estimates and linear trends is around 1 kg m−2 RMS and ± 0.3 kg m−2 per decade, respectively. Standardized methods for ZTD outlier detection and IWV conversion are proposed. The homogeneity of final time series is limited however by changes in the stations equipment and environment. Various homogenization algorithms have been evaluated based on a synthetic benchmark dataset. The uncertainty of trends estimated from the homogenized times series is estimated to ±0.5 kg m−2 per decade. Reprocessed GNSS IWV data are analysed along with satellites data, reanalyses and global and regional climate model simulations. A selection of global and regional reprocessed GNSS datasets and ERA-interim reanalysis are made available through the GOP-TropDB tropospheric database and online service. A new tropo SINEX format, providing new features and simplifications, was developed and it is going to be adopted by all the IAG services. Numéro de notice : H2020-001 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Chapître / contribution nature-HAL : ChOuvrScient DOI : 10.1007/978-3-030-13901-8_5 date de publication en ligne : 14/09/2019 En ligne : https://doi.org/10.1007/978-3-030-13901-8_5 Format de la ressource électronique : URL chapitre Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94504

Advanced GNSS tropospheric products for monitoring severe weather events and climate / Jonathan Jones (2020)  

Public Titre : Advanced GNSS tropospheric products for monitoring severe weather events and climate : COST action ES1206 final action dissemination report Type de document : Actes de congrès Auteurs : Jonathan Jones, Editeur scientifique ; Guergana Guerova, Editeur scientifique ; Jan Douša, Editeur scientifique ; Galina Dick, Editeur scientifique ; Siebren de Haan, Editeur scientifique ; Eric Pottiaux, Editeur scientifique ; Olivier Bock , Editeur scientifique ; Rosa Pacione, Editeur scientifique ; Roeland Van Malderen, Editeur scientifique Editeur : Berlin, Heidelberg, Vienne, New York, ... : Springer Année de publication : 2020 Projets : GNSS4SWEC / Importance : 563 p. ISBN/ISSN/EAN : 978-3-030-13901-8 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] changement climatique [Termes IGN] climat terrestre [Termes IGN] données GNSS [Termes IGN] données météorologiques [Termes IGN] positionnement par GNSS [Termes IGN] propagation troposphérique [Termes IGN] surveillance météorologique [Termes IGN] vapeur d'eau Résumé : (Editeur) [Introduction] The book (COST Action Final report) summarises the proceedings from COST Action ES1206. COST Action ES1206, Advanced GNSS Tropospheric Products for Severe Weather Events and Climate (GNSS4SWEC), was a 4-year project, running from 2013 to 2017, which coordinated new and improved capabilities from concurrent developments in GNSS, meteorological and climate communities. For the first time, the synergy of multi-GNSS constellations was used to develop new, more advanced tropospheric products, exploiting the full potential of multi-GNSS on a wide range of temporal and spatial scales - from real-time products monitoring and forecasting severe weather, to the highest quality post-processed products suitable for climate research. The Action also promoted the use of meteorological data as an input to real-time GNSS positioning, navigation, and timing services and has stimulated knowledge and data transfer throughout Europe and beyond. Note de contenu : - Front Matter - General Background - Advanced GNSS Processing Techniques (Working Group 1) - Use of GNSS Tropospheric Products for High-Resolution, Rapid-Update NWP and Severe Weather Forecasting (Working Group 2) - Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3) - National Status Reports - STSM Reports - Back Matter Numéro de notice : 26248 Affiliation des auteurs : Géodésie+Ext (mi2018-2019) Thématique : POSITIONNEMENT Nature : Actes nature-HAL : DirectOuvrColl/Actes DOI : 10.1007/978-3-030-13901-8 date de publication en ligne : 14/09/2019 En ligne : https://doi.org/10.1007/978-3-030-13901-8 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94503

Contient

• Advanced GNSS tropospheric products for monitoring severe weather events and climate, ch. 5. Use of GNSS Tropospheric Products for Climate Monitoring (Working Group 3) / Olivier Bock (2020)  

A new segmentation method for the homogenisation of GNSS-derived IWV time-series / Annarosa Quarello (2020)  

Public contenu dans ArXiv / Université Cornell (Etats-Unis) (1991)   Titre : A new segmentation method for the homogenisation of GNSS-derived IWV time-series Type de document : Article/Communication Auteurs : Annarosa Quarello , Auteur ; Olivier Bock , Auteur ; Emilie Lebarbier, Auteur Editeur : Ithaca [New York - Etats-Unis] : ArXiv - Université Cornell Année de publication : 2020 Importance : 25 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] algorithme d'homogénéisation [Termes IGN] analyse de variance [Termes IGN] changement climatique [Termes IGN] données GNSS [Termes IGN] estimateur [Termes IGN] inférence [Termes IGN] itération [Termes IGN] positionnement ponctuel précis [Termes IGN] programmation dynamique [Termes IGN] série temporelle [Termes IGN] surveillance météorologique [Termes IGN] teneur intégrée en vapeur d'eau [Termes IGN] variation saisonnière Résumé : (auteur) Homogenization is an important and crucial step to improve the usage of observational data for climate analysis. This work is motivated by the analysis of long series of GNSS Integrated Water Vapour (IWV) data which have not yet been used in this context. This paper proposes a novel segmentation method that integrates a periodic bias and a heterogeneous, monthly varying, variance. The method consists in estimating first the variance using a robust estimator and then estimating the segmentation and periodic bias iteratively. This strategy allows for the use of the dynamic programming algorithm that remains the most efficient exact algorithm to estimate the change-point positions. The statistical performance of the method is assessed through numerical experiments. An application to a real data set of 120 global GNSS stations is presented. The method is implemented in the R package GNSSseg that will be available on the CRAN. Numéro de notice : P2020-005 Affiliation des auteurs : UMR IPGP-Géod+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Preprint nature-HAL : Préprint DOI : sans En ligne : https://arxiv.org/pdf/2005.04683.pdf Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95078

Toward global soil moisture monitoring with sentinel-1 : harnessing assets and overcoming obstacles / Bernhard Bauer-Marschallinger in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 57 n° 1 (January 2019) . - pp 520 - 539 Titre : Toward global soil moisture monitoring with sentinel-1 : harnessing assets and overcoming obstacles Type de document : Article/Communication Auteurs : Bernhard Bauer-Marschallinger, Auteur ; Vahid Freeman, Auteur ; Senmao Cao, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 520 - 539 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] bande C [Termes IGN] bilan hydrique [Termes IGN] humidité du sol [Termes IGN] image radar moirée [Termes IGN] image Sentinel-SAR [Termes IGN] Italie [Termes IGN] Ombrie (Italie) [Termes IGN] surveillance agricole [Termes IGN] surveillance météorologique Résumé : (Auteur) Soil moisture is a key environmental variable, important to, e.g., farmers, meteorologists, and disaster management units. Here, we present a method to retrieve surface soil moisture (SSM) from the Sentinel-1 (S-1) satellites, which carry C-band Synthetic Aperture Radar (CSAR) sensors that provide the richest freely available SAR data source so far, unprecedented in accuracy and coverage. Our SSM retrieval method, adapting well-established change detection algorithms, builds the first globally deployable soil moisture observation data set with 1-km resolution. This paper provides an algorithm formulation to be operated in data cube architectures and high-performance computing environments. It includes the novel dynamic Gaussian upscaling method for spatial upscaling of SAR imagery, harnessing its field-scale information and successfully mitigating effects from the SAR's high signal complexity. Also, a new regression-based approach for estimating the radar slope is defined, coping with Sentinel-1's inhomogeneity in spatial coverage. We employ the S-1 SSM algorithm on a 3-year S-1 data cube over Italy, obtaining a consistent set of model parameters and product masks, unperturbed by coverage discontinuities. An evaluation of therefrom generated S-1 SSM data, involving a 1-km soil water balance model over Umbria, yields high agreement over plains and agricultural areas, with low agreement over forests and strong topography. While positive biases during the growing season are detected, the excellent capability to capture small-scale soil moisture changes as from rainfall or irrigation is evident. The S-1 SSM is currently in preparation toward operational product dissemination in the Copernicus Global Land Service. Numéro de notice : A2019-108 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2018.2858004 date de publication en ligne : 22/08/2018 En ligne : https://doi.org/10.1109/TGRS.2018.2858004 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92425 [article]

Bilan de l’Action COST ES1206 - GNSS4SWEC (Advanced Global Navigation Satellite Systems tropospheric products for monitoring severe weather events and climate) / Olivier Bock (2018)

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Homogeneizing GPS integrated water vapour time series: methodology and benchmarking the algorithms on synthetic datasets / Roeland Van Malderen (2017)    

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Real-time GPS precise point positioning-based precipitable water vapor estimation for rainfall monitoring and forecasting / Junbo Shi in IEEE Transactions on geoscience and remote sensing, vol 53 n° 6 (June 2015)  

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Utilisation de la corrélation d’images dans les géosciences / Boris Leroux (2014) 

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Martinique : un site surveillé / Michel Ravelet in Géomètre, n° 2107 (octobre 2013)

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Monitoring precipitable water vapor in real-time using global navigation satellite systems / Seung-Woo Lee in Journal of geodesy, vol 87 n° 10-12 (October - December 2013)  

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Apport du système de navigation GLONASS à la surveillance de l'ionosphère au dessus de l'Europe / Emilie Pelletier (2013) 

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Monitoring seasonal snow dynamics using ground based high resolution photography (Austre Lovénbreen, Svalbard, 79°N) / Etienne Bernard in ISPRS Journal of photogrammetry and remote sensing, vol 75 (January 2013)

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Near real-time estimation of water vapour in the troposphere using ground GNSS and the meteorological data / Jaroslaw Bosy in Annales Geophysicae, n° 30 (27/09/2012)  

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Identification and modelling of sea level change contributors on GRACE satellite gravity data and their applications to climate monitoring / Bert Wouters (2010)

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