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Shore zone classification from ICESat-2 data over Saint Lawrence Island / Huan Xie in Marine geodesy, vol 44 n° 5 (September 2021)  

Public [article]  inMarine geodesy > vol 44 n° 5 (September 2021) . - pp 454 - 466 Titre : Shore zone classification from ICESat-2 data over Saint Lawrence Island Type de document : Article/Communication Auteurs : Huan Xie, Auteur ; Yuan Sun, Auteur ; Xiaoshuai Liu, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 454 - 466 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Lasergrammétrie [Termes IGN] Alaska (Etats-Unis) [Termes IGN] Bering, mer de [Termes IGN] données ICEsat [Termes IGN] Google Earth [Termes IGN] indicateur environnemental [Termes IGN] littoral [Termes IGN] modèle de régression [Termes IGN] photon [Termes IGN] sédiment Résumé : (Auteur) The shore zone is the most active zone in the atmosphere, hydrosphere, biosphere and lithosphere of nature, and has the environmental characteristics of both ocean and land. The ICESat-2 satellite provides height measurements of shore zone using a photon-counting LiDAR. The purpose of this study is to explore the application potential of ICESat-2 satellite data in shore zone classification. Saint Lawrence Island, Alaska, was chosen as the study area. Firstly, in this study, the upper and lower boundaries of the shore zone of the study area were extracted based on Google Earth images. The slope and width between the two boundaries were then calculated according to the formula. Secondly, six statistical indicators (standard deviation, relative standard deviation, average absolute deviation, relative average deviation, absolute median error and quartile deviation) related to the substrate and sediment classification that could reflect the characteristics of the shore zone profile were extracted, and the statistical indicators were used as input parameters of the softmax regression model for classification. Finally, the accuracy of the shore zone classification was validated using the ShoreZone classification system. The results show that, among the 246 shore zone sections in the study area, 86% (212) has been correctly classified. The results therefore indicate that ICESat-2 data can be used to support the characterization of shore zone morphology. Numéro de notice : A2021-578 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/01490419.2021.1898498 date de publication en ligne : 29/03/2021 En ligne : https://doi.org/10.1080/01490419.2021.1898498 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98234 [article]

Ionospheric irregularity layer height and thickness estimation with a GNSS receiver array / Seebany Datta-Barua in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 7 (July 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > Vol 59 n° 7 (July 2021) . - pp 6198 - 6207 Titre : Ionospheric irregularity layer height and thickness estimation with a GNSS receiver array Type de document : Article/Communication Auteurs : Seebany Datta-Barua, Auteur ; Yang Su, Auteur ; Aurora López Rubio, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 6198 - 6207 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] Alaska (Etats-Unis) [Termes IGN] hauteur de la couche ionosphérique [Termes IGN] méthode de Monte-Carlo [Termes IGN] modèle ionosphérique [Termes IGN] phase GNSS [Termes IGN] rapport signal sur bruit [Termes IGN] scintillation [Termes IGN] série temporelle [Termes IGN] signal GNSS Résumé : (auteur) This work develops a method by which a kilometer-spaced array of Global Navigation Satellite System (GNSS) scintillation receivers can be used to estimate the ionospheric irregularity layer height and thickness and associated uncertainties on those estimates. Spectra of filtered signal power and phase data are used to estimate these quantities by comparing the observed ratio of the log of the power spectrum to the phase spectrum with the Rytov weak scatter theoretical ratio. A Monte Carlo simulation of noise on the input signal and the irregularity drift velocity is used to quantify the error in estimates of height and thickness. The method is tested using data from the Scintillation Auroral Global Positioning System (GPS) Array (SAGA) sited in the auroral zone at Poker Flat Research Range, Alaska. For the 30-min scintillation period studied, the technique identifies ionospheric scattering from a thick F layer, which correlates well with on-site incoherent scatter radar measurements of peak electron density, for an event previously identified in the literature as likely due to F layer. Numéro de notice : A2021-539 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1109/TGRS.2020.3024173 date de publication en ligne : 12/10/2020 En ligne : https://doi.org/10.1109/TGRS.2020.3024173 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98013 [article]

A novel unsupervised change detection method from remotely sensed imagery based on an improved thresholding algorithm / Sara Khanbani in Applied geomatics, vol 13 n° 1 (May 2021)  

Public [article]  inApplied geomatics > vol 13 n° 1 (May 2021) . - pp 89 - 105 Titre : A novel unsupervised change detection method from remotely sensed imagery based on an improved thresholding algorithm Type de document : Article/Communication Auteurs : Sara Khanbani, Auteur ; Ali Mohammadzadeh, Auteur ; Milad Janalipour, Auteur Année de publication : 2021 Article en page(s) : pp 89 - 105 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] Alaska (Etats-Unis) [Termes IGN] algorithme génétique [Termes IGN] changement temporel [Termes IGN] classification floue [Termes IGN] classification non dirigée [Termes IGN] classification par nuées dynamiques [Termes IGN] coût [Termes IGN] détection de changement [Termes IGN] seuillage Résumé : (auteur) Change Detection (CD) problem from remotely sensed images is a popular topic among researchers. Because of the diversity in the problem of change detection and the complexity of the study areas it cannot be claimed that there is an appropriate and prevalent algorithm which is more effective for different types of the case study. As a fundamental investigation, it is critical to recognize the weaknesses of the state of artworks in change detection. Also, those examined weaknesses have to be improved aptly to develop a new strong method. This paper presents a thresholding algorithm improved by the Genetic Algorithm (GA) in CD problems, which focuses on minimizing a novel cost function. The suggested cost function can be adopted for local and global change variations in difference images without any prior assumptions. The presented algorithm was tested on two data sets (i.e., Alaska region and Uremia Lake) to validate its effectiveness. Experimental results demonstrated that the proposed algorithm in this work has improved the accuracy of change detection (changed pixel accuracy term) in the Alaska region about 8%–12% and also in Uremia Lake approximately between 8%–13% in comparison with other conventional methods including Fuzzy C- Means (FCM), Otsu thresholding, K-Means, and K-Medoid. Numéro de notice : A2021-237 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article DOI : 10.1007/s12518-020-00323-6 date de publication en ligne : 22/06/2020 En ligne : https://doi.org/10.1007/s12518-020-00323-6 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97246 [article]

A systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems / Dong Chen in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)  

Public [article]  inISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 63 - 77 Titre : A systematic evaluation of influence of image selection process on remote sensing-based burn severity indices in North American boreal forest and tundra ecosystems Type de document : Article/Communication Auteurs : Dong Chen, Auteur ; Tatiana V. Loboda, Auteur ; Joanne V. Hall, Auteur Année de publication : 2020 Article en page(s) : pp 63 - 77 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Alaska (Etats-Unis) [Termes IGN] Canada [Termes IGN] changement climatique [Termes IGN] écosystème forestier [Termes IGN] forêt boréale [Termes IGN] image Landsat [Termes IGN] incendie de forêt [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] perturbation écologique [Termes IGN] Short Waves InfraRed [Termes IGN] toundra Résumé : (Auteur) Satellite imagery has been widely used for the assessment of wildfire burn severity within the scientific community and fire management agencies. Multiple indices have been proposed to assess burn severity, among which the differenced Normalized Burn Ratio (dNBR) is arguably the most commonly used index that is expected to provide an objective and consistent assessment. However, although evidence of variability in the dNBR-based assessment of burn severity driven by image pair selection has been shown in many studies, the comprehensive examination of the extent of the bias resulting from the image selection has been lacking. In this study, we focus on three factors of the image selection process which are encountered by most Landsat-derived dNBR applications, including the sensor combination and the difference in timing of image acquisition (for both the year and seasonality) of pre- and post-fire image pairs. Through separate analyses, each targeting a single factor, we show that Landsat sensor combination between the pre- and post-fire images has a limited impact on the dNBR values. The difference in the year of acquisition between the images in the image pairs is shown to influence dNBR assessment with a noticeable increase in mean dNBR (>0.1) with only a single year difference between images compared to multi-year differences. However, differences in the image acquisition seasons and the resulting phenological differences is shown to impact dNBR values most considerably. Based on our results, we warn against the calculation of dNBR when the images are acquired in different seasons. We believe that despite the existence of multiple derivatives of dNBR, there remains a need for an improved version; one that is less susceptible to the phenological impacts introduced by the selected images. Numéro de notice : A2020-012 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.011 date de publication en ligne : 19/11/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.011 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94400 [article]

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Co-seismic displacement and waveforms of the 2018 Alaska earthquake from high-rate GPS PPP velocity estimation / Shuanggen Jin in Journal of geodesy, vol 93 n° 9 (September 2019)  

Public [article]  inJournal of geodesy > vol 93 n° 9 (September 2019) . - pp 1559 - 1569 Titre : Co-seismic displacement and waveforms of the 2018 Alaska earthquake from high-rate GPS PPP velocity estimation Type de document : Article/Communication Auteurs : Shuanggen Jin, Auteur ; Ke Su, Auteur Année de publication : 2019 Article en page(s) : pp 1559 - 1569 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] Alaska (Etats-Unis) [Termes IGN] déformation de la croute terrestre [Termes IGN] positionnement cinématique [Termes IGN] positionnement ponctuel précis [Termes IGN] séisme [Termes IGN] vitesse de déplacement Résumé : (Auteur) For earthquake and tsunami early warning and emergency response, the parameters of earthquakes should be determined rapidly and correctly. The precise displacement time series can be obtained from high-rate GPS precise point positioning (PPP) during the earthquake, but require long convergence time. In this paper, the PPP velocity estimation (PPPVE) approach is applied to estimate the velocity waveforms and integrate to displacement waveforms in real-time scenarios. A case study of the 2018 Alaska earthquake is conducted from 1 Hz GPS data. The accuracy of velocity and displacement waveforms for 1 Hz GPS data is analyzed by comparing PPPVE-derived displacements with kinematic PPP solution. The results indicate that PPP and PPPVE are both capable of detecting seismic displacement waveforms with amplitude of 1 cm horizontally, while PPPVE can detect the displacement waveforms with much faster convergence speed. The mean convergence time of PPPVE for north, east and up components are 19, 22 and 31 s, respectively. The derived ground motion parameters estimate a magnitude of Mw = 7.97 ± 0.18, showing a great consistency and agreement with the seismometer magnitude. The preliminary relationship between the seismic intensity and ground motion parameters is established and evaluated for an auxiliary reference. Furthermore, the permanent displacement induced by the earthquake is obtained from real-time PPPVE approach. The benefits of PPPVE approach for GNSS seismology are demonstrated. Numéro de notice : A2019-506 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-019-01269-3 date de publication en ligne : 24/06/2019 En ligne : https://doi.org/10.1007/s00190-019-01269-3 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93789 [article]

Combining potentially incompatible community datasets when harmonizing forest inventories in subarctic Alaska, USA / Robert J. Smith in Journal of vegetation science, vol 30 n° 1 (January 2019)  

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Remote sensing of environmental changes in cold regions / Jinyang Du (2019)  

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Integrating SAR and derived products into operational volcano monitoring and decision support systems / Franz J. Meyer in ISPRS Journal of photogrammetry and remote sensing, vol 100 (February 2015)  

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Illustrating the temporal progress of environmental change / Joann W. Harvey in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 12 (December 2013)  

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Landscape controls over major nutrients and primary productivity of Arctic lakes / P. Pathak in Cartography and Geographic Information Science, vol 39 n° 4 (October 2012)  

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Producing an indigenous knowledge Web GIS for Arctic Alaska communities: Challenges, successes, and lessons learned / W. Eisner in Transactions in GIS, vol 16 n° 1 (February 2012)  

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Mapping vegetated wetlands of Alaska using L-band radar satellite imagery / Jane Whitcomb in Canadian journal of remote sensing, vol 35 n° 1 (February 2009)

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DEM control in Arctic Alaska with Icesat laser altimetry / D.K. Atwood in IEEE Transactions on geoscience and remote sensing, vol 45 n° 11 Tome 2 (November 2007)

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InSAR imaging of volcanic deformation over cloud-prone areas: Aleutian islands / Zhong Lu in Photogrammetric Engineering & Remote Sensing, PERS, vol 73 n° 3 (March 2007)

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March2003 EOS aqua AMSR-E sea ice field campaign / D.J. Cavalieri in IEEE Transactions on geoscience and remote sensing, vol 44 n° 11 Tome 1 (November 2006)

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