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Exploration and analysis of the factors influencing GNSS PWV for nowcasting applications / Min Guo in Advances in space research, vol 67 n° 12 (15 June 2021)
[article]
Titre : Exploration and analysis of the factors influencing GNSS PWV for nowcasting applications Type de document : Article/Communication Auteurs : Min Guo, Auteur ; Hanwei Zhang, Auteur ; Pengfei Xia, Auteur Année de publication : 2021 Article en page(s) : pp 3960 - 3978 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] brouillard
[Termes IGN] données GNSS
[Termes IGN] données météorologiques
[Termes IGN] Pékin (Chine)
[Termes IGN] retard troposphérique zénithal
[Termes IGN] surveillance météorologique
[Termes IGN] température de surface
[Termes IGN] vapeur d'eauRésumé : (auteur) Precipitable water vapor (PWV) can be assimilated into a numerical weather model (NWM) to improve the prediction accuracy of numerical weather prediction. In this study, taking GNSS data for the Beijing Fangshan station (BJFS) as an example, based on the method of Pearson correlation coefficient combined with quantitative analysis, GNSS datasets are used to study the relationships between GNSS-derived PWV (GNSS PWV_Met) and its influencing factors, including the internal influencing factors zenith troposphere delay (ZTD), zenith hydrostatic delay (ZHD), zenith wet delay (ZWD), and surface temperature (Ts), and the external influencing factor haze (mainly PM2.5). Firstly, based on the strong correlation between PWV_Met and ZTD hourly sequences from the International GNSS Service Network’s BJFS station for DOYS 182–212, 2015, the results of experiment prove that the reliability of GNSS ZTD is used to forecast PWV_Met in short-term forecasting. Secondly, based on hourly data of BJFS in 2016, the correlation between PWV_Met and ZTD, ZWD, ZHD, pressure (P) and Ts is analyzed, and then, with the rate of ZTD variation as the main factor, ZTD variation as auxiliary factor, the prediction success rate is 88.24% from hourly data of precipitation event for DOYs 183–213 in Beijing. The experiment indicates that ZTD can help forecast short-term precipitation. Thirdly, based on data from three hazy periods with relatively stable weather conditions, no heavy rainfall, and relatively continuous data in the past three years, the correlation between GNSS PWV_Met/ZTD and PM2.5 hourly series is analyzed. The results of the experiments suggests that GNSS ZTD should be considered to assist in haze monitoring. So in the absence of radiosonde stations and meteorological elements, ZTDs on retrieval of GNSS stations have more application value in short-term forecast. Numéro de notice : A2021-947 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1016/j.asr.2021.02.018 Date de publication en ligne : 06/05/2021 En ligne : https://doi.org/10.1016/j.asr.2021.02.018 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99763
in Advances in space research > vol 67 n° 12 (15 June 2021) . - pp 3960 - 3978[article]Urban classification by the fusion of thermal infrared hyperspectral and visible data / Jiayi Li in Photogrammetric Engineering & Remote Sensing, PERS, vol 81 n° 12 (December 2015)
[article]
Titre : Urban classification by the fusion of thermal infrared hyperspectral and visible data Type de document : Article/Communication Auteurs : Jiayi Li, Auteur ; Hongyan Zhang, Auteur ; Min Guo, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 901 - 911 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image numérique
[Termes IGN] bande spectrale
[Termes IGN] bande visible
[Termes IGN] classification dirigée
[Termes IGN] fusion de données
[Termes IGN] image hyperspectrale
[Termes IGN] image thermique
[Termes IGN] occupation du solRésumé : (auteur) The 2014 Data Fusion Contest, organized by the Image Analysis and Data Fusion (IADF) Technical Committee of the IEEE Geoscience and Remote Sensing Society, involved two datasets acquired at different spectral ranges and spatial resolutions: a coarser-resolution long-wave infrared (LWIR, thermal infrared) hyperspectral data set and fine-resolution data acquired in the visible (VIS) wavelength range. In this article, a novel multi-level fusion approach is proposed to fully utilize the characteristics of these two different datasets to achieve improved urban land-use and land-cover classification. Specifically, road extraction by fusing the classification result of the TI-HSI dataset and the segmentation result of the VIS dataset is first proposed. Thereafter, a novel gap inpainting method for the VIS data with the guidance of the TI-HSI data is presented to deal with the swath width inconsistency, and to facilitate an accurate spatial feature extraction step. The experimental results with the 2014 Data Fusion Contest datasets suggest that the proposed method can alleviate the multi-spectral-spatial resolution and multi-swath width problem to a great extent, and achieve an improved urban classification accuracy. Numéro de notice : A2015-990 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.14358/PERS.81.12.901 En ligne : https://doi.org/10.14358/PERS.81.12.901 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=80271
in Photogrammetric Engineering & Remote Sensing, PERS > vol 81 n° 12 (December 2015) . - pp 901 - 911[article]