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Diffuse sunlight and cosmic rays: Missing pieces of the forest growth change attribution puzzle? / Jean-Daniel Bontemps in Science of the total environment, vol 806 n°1 (February 2022)  

Public [article]  inScience of the total environment > vol 806 n°1 (February 2022) . - n° 150469 Titre : Diffuse sunlight and cosmic rays: Missing pieces of the forest growth change attribution puzzle? Type de document : Article/Communication Auteurs : Jean-Daniel Bontemps , Auteur ; Henrik Svensmark, Auteur Année de publication : 2022 Projets : 1-Pas de projet / Article en page(s) : n° 150469 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cerne [Termes IGN] croissance des arbres [Termes IGN] dioxyde de carbone [Termes IGN] modèle de croissance végétale [Termes IGN] modélisation de la forêt [Termes IGN] photosynthèse [Termes IGN] rayonnement cosmique [Termes IGN] rayonnement lumineux [Vedettes matières IGN] Végétation et changement climatique Résumé : (auteur) Forest growth changes have been a matter of intense research efforts since the 1980s. Owing to the variety of their environmental causes – mainly atmospheric CO2 increase, atmospheric N deposition, changes in temperature and water availability, and their interactions – their interpretation has remained challenging. Recent isolated researches suggest further effects of neglected environmental factors, namely changes in the diffuse fraction of light, more efficient to photosynthesis, and galactic cosmic rays (GCR), both emphasized in this Discussion paper. With growing awareness of GCR influence on global cloudiness (the cosmoclimatologic theory by H. Svensmark), GCR may thus cause trends in diffuse-light, and distinguishing between their direct/indirect influences on forest growth remains uncertain. This link between cosmic rays and diffuse sunlight also forms an alternative explanation to the geological evidence of a negative correlation between GCR and atmospheric CO2 concentration over the past 500 Myr. After a careful scrutiny of this literature and of key contributions in the field, we draw research options to progress further in this attribution. These include i) observational strategies intending to build on differences in the spatio-temporal dynamics of environmental growth factors, ranging from quasi-experiments to meta-analyses, ii) simulation strategies intending to quantify environmental factor's effects based on process-based ecosystem modelling, in a context where progresses for accounting for diffuse-light fraction are ongoing. Also, the hunt for tree-ring based proxies of GCR may offer the perspective of testing the GCR hypothesis on fully coupled forest growth samples. Numéro de notice : A2022-001 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.scitotenv.2021.150469 date de publication en ligne : 21/09/2021 En ligne : https://doi.org/10.1016/j.scitotenv.2021.150469 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98515 [article]

Atmospheric correction to passive microwave brightness temperature in snow cover mapping over china / Yubao Qiu in IEEE Transactions on geoscience and remote sensing, vol 59 n° 8 (August 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 8 (August 2021) . - pp 6482 - 6495 Titre : Atmospheric correction to passive microwave brightness temperature in snow cover mapping over china Type de document : Article/Communication Auteurs : Yubao Qiu, Auteur ; Lijuan Shi, Auteur ; Juha Lemmetyinen, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6482 - 6495 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] capteur passif [Termes IGN] Chine [Termes IGN] correction atmosphérique [Termes IGN] image NOAA [Termes IGN] image SSMIS [Termes IGN] image Terra-MODIS [Termes IGN] manteau neigeux [Termes IGN] modèle atmosphérique [Termes IGN] neige [Termes IGN] série temporelle [Termes IGN] télédétection en hyperfréquence [Termes IGN] température de luminance [Termes IGN] teneur en vapeur d'eau Résumé : (auteur) Variable atmospheric conditions are typically ignored in the retrieval of geophysical parameters of the Earth’s surface when using spaceborne passive microwave observations. However, high frequencies, for example, 91.7 GHz, are sensitive to variable atmospheric absorption, even in winter’s dry conditions. In this article, the influence of variable atmospheric absorption on snow cover extent (SCE) mapping was quantitatively investigated. A physical method was derived to enable atmospheric correction for variable atmospheric conditions. The total column precipitable water vapor (TPWV) from Moderate Resolution Imaging Spectroradiometer (MODIS) was parametrized into transmittances in this correction method. The corrected brightness temperature at 19 and 91.7 GHz from the Special Sensor Microwave Imager Sounder (SSMIS) was applied to the threshold algorithm for snow mapping over China. Compared with the Interactive Multisensor Snow and Ice Mapping System (IMS) data in winter from 2012 to 2013, for Qinghai–Tibet plateau (QTP), a significant improvement after correction was obtained from February to March over ephemeral and shallow snow, where the largest daily improvement of accuracy is up to 20%. The accuracy (incl. precision, recall, and F1 index) improved on average is from 0.77 (0.60, 0.68, and 0.63) to 0.79 (0.69, 0.7, and 0.68) over the full winter time from December to March. Over forest-rich Northeast China, where snow in winter is thicker, small improvement was observed at the onset of the snow season and over snow margin area. It was evidenced that high frequency is a promising way of snow cover mapping with the proposed atmospheric correction method. Numéro de notice : A2021-630 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2020.3031837 date de publication en ligne : 02/11/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3031837 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98279 [article]

Extraction of urban built-up areas from nighttime lights using artificial neural network / Tingting Xu in Geocarto international, vol 35 n° 10 ([01/08/2020])  

Public [article]  inGeocarto international > vol 35 n° 10 [01/08/2020] . - pp 1049 - 1066 Titre : Extraction of urban built-up areas from nighttime lights using artificial neural network Type de document : Article/Communication Auteurs : Tingting Xu, Auteur ; Giovanni Coco, Auteur ; Jay Gao, Auteur Année de publication : 2020 Article en page(s) : pp 1049 - 1066 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] aménagement du territoire [Termes IGN] bati [Termes IGN] cartographie urbaine [Termes IGN] classification dirigée [Termes IGN] développement durable [Termes IGN] échantillonnage [Termes IGN] éclairage public [Termes IGN] extraction de traits caractéristiques [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] rayonnement lumineux [Termes IGN] réseau neuronal artificiel [Termes IGN] seuillage [Termes IGN] température au sol [Termes IGN] zone urbaine Résumé : (auteur) The spatial distribution of urban areas at the national and regional scales is critical for urban planners and governments to design sustainable and environment-friendly future development plans. The nighttime lights (NTL) data provide an effective way to monitor the urban at different scales however is usually achieved by using empirical threshold-based algorithms. This study proposed a novel Artificial Neural Network (ANN) approach, using moderate resolution imageries as NTL, MODIS NDVI and land surface temperature data, to map urban areas. Both random and maximum dissimilarity distance algorithm sampling methods were considered and compared. The validation of the urban areas extracted from MDA-based ANN against the 2011 US national land cover data showed a reasonable quality (overall accuracy = 97.84; Kappa = 0.74) and achieved more accurate result than the threshold method. This study demonstrates that ANN can provide an effective, rapid, and accurate alternative in extracting urban built-up areas from NTL. Numéro de notice : A2020-424 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/10106049.2018.1559887 date de publication en ligne : 21/03/2019 En ligne : https://doi.org/10.1080/10106049.2018.1559887 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95488 [article]

Improved depth estimation for occlusion scenes using a light-field camera / Changkun Yang in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 7 (July 2020)  

Public [article]  inPhotogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 7 (July 2020) . - pp 443-456 Titre : Improved depth estimation for occlusion scenes using a light-field camera Type de document : Article/Communication Auteurs : Changkun Yang, Auteur ; Zhaoqin Liu, Auteur ; Kaichang Di, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 443-456 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] approche pixel [Termes IGN] caméra numérique [Termes IGN] détection de partie cachée [Termes IGN] disparité [Termes IGN] effet de profondeur cinétique [Termes IGN] lentille [Termes IGN] méthode de centrage [Termes IGN] rayonnement lumineux [Termes IGN] reconstruction 3D Résumé : (Auteur) With the development of light-field imaging technology, depth estimation using light-field cameras has become a hot topic in recent years. Even through many algorithms have achieved good performance for depth estimation using light-field cameras, removing the influence of occlusion, especially multi-occlusion, is still a challenging task. The photo-consistency assumption does not hold in the presence of occlusions, which makes most depth estimation of light-field imaging unreliable. In this article, a novel method to handle complex occlusion in depth estimation of light-field imaging is proposed. The method can effectively identify occluded pixels using a refocusing algorithm, accurately select unoccluded views using the adaptive unoccluded-view identification algorithm, and then improve the depth estimation by computing the cost volumes in the unoccluded views. Experimental results demonstrate the advantages of our proposed algorithm compared with conventional state-of-the art algorithms on both synthetic and real light-field data sets. Numéro de notice : A2020-383 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.7.443 date de publication en ligne : 01/07/2020 En ligne : https://doi.org/10.14358/PERS.86.7.443 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95430 [article]

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10th Colour and Visual Computing Symposium 2020 (CVCS 2020), Gjøvik, Norway, and Virtual, September 16-17, 2020 / Jean-Baptiste Thomas (2020)  

Public Titre : 10th Colour and Visual Computing Symposium 2020 (CVCS 2020), Gjøvik, Norway, and Virtual, September 16-17, 2020 : Proceedings Type de document : Actes de congrès Auteurs : Jean-Baptiste Thomas, Éditeur scientifique Congrès : Congrès: CVCS 2020 Colour and Visual Computing Symposium 2020 (September 16-17, 2020; Gjøvik, Norvège), Auteur Editeur : Gjøvik [Norvège] : Norwegian University of Science and Technology Année de publication : 2020 Conférence : CVCS 2020, Colour and Visual Computing Symposium 16/09/2020 17/09/2020 Gjøvik et en ligne Norvège Open Access Proceedings Langues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] analyse linéaire des mélanges spectraux [Termes IGN] analyse visuelle [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] couleur (variable spectrale) [Termes IGN] distribution du coefficient de réflexion bidirectionnelle BRDF [Termes IGN] image hyperspectrale [Termes IGN] image multibande [Termes IGN] imagerie médicale [Termes IGN] luminance lumineuse [Termes IGN] peinture [Termes IGN] photographie Numéro de notice : 25892 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Actes En ligne : http://ceur-ws.org/Vol-2688/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96006

Caractérisation du manteau neigeux arctique, suivi climatique et télédétection micro-onde / Céline Vargel (2020)  

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Improved algorithms for the measurement of total precipitable water and cloud liquid water from SARAL microwave radiometer observations / Rajput Neha Mangalsinh in Marine geodesy, vol 42 n° 4 (July 2019)  

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Evaluating metrics derived from Landsat 8 OLI imagery to map crop cover / Rei Sonobe in Geocarto international, vol 34 n° 8 ([15/06/2019])  

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Improving the spatial bias correction algorithm in SMOS image reconstruction processor : validation of soil moisture retrievals with in situ data / Ali Khazaal in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)  

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Machine learning for image segmentation / Kaiwen Chang (2019)  

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EMVS : Event-based Multi-View Stereo : 3D reconstruction with an event camera in real-time / Henri Rebecq in International journal of computer vision, vol 126 n° 12 (December 2018)  

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Visible + Near Infrared spectroscopy as taxonomic tool for identifying birch species / Mulualem Tigabu in Silva fennica, vol 52 n° 4 (September 2018)  

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Wind loads and competition for light sculpt trees into self-similar structures / Christophe Eloy in Nature communications, vol 8 (2017)  

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Forestry applications of UAVs in Europe: a review / Chiara Torresan in International Journal of Remote Sensing IJRS, vol 38 n° 8-10 (April 2017)  

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Télédétection pour l'observation des surfaces continentales, Volume 3. Observation des surfaces continentales par télédétection 1 / Nicolas Baghdadi (2017)

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