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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)
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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 descripteurs IGN] Alaska (Etats-Unis)
[Termes descripteurs IGN] Canada
[Termes descripteurs IGN] changement climatique
[Termes descripteurs IGN] écosystème forestier
[Termes descripteurs IGN] forêt boréale
[Termes descripteurs IGN] image Landsat
[Termes descripteurs IGN] incendie de forêt
[Termes descripteurs IGN] Normalized Difference Vegetation Index
[Termes descripteurs IGN] perturbation écologique
[Termes descripteurs IGN] Short Waves InfraRed
[Termes descripteurs IGN] toundraRésumé : (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
in ISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 63 - 77[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2020011 SL Revue Centre de documentation Revues en salle Disponible 081-2020013 DEP-RECP Revue MATIS Dépôt en unité Exclu du prêt 081-2020012 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt 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)
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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 descripteurs IGN] Alaska (Etats-Unis)
[Termes descripteurs IGN] déformation de la croute terrestre
[Termes descripteurs IGN] positionnement cinématique
[Termes descripteurs IGN] positionnement ponctuel précis
[Termes descripteurs IGN] séisme
[Termes descripteurs IGN] vitesse de déplacementRésumé : (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
in Journal of geodesy > vol 93 n° 9 (September 2019) . - pp 1559 - 1569[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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Titre : Combining potentially incompatible community datasets when harmonizing forest inventories in subarctic Alaska, USA Type de document : Article/Communication Auteurs : Robert J. Smith, Auteur ; Andrew N. Gray, Auteur Année de publication : 2019 Article en page(s) : pp 18 - 29 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] Alaska (Etats-Unis)
[Termes descripteurs IGN] forêt boréale
[Termes descripteurs IGN] inventaire forestier (techniques et méthodes)
[Termes descripteurs IGN] inventaire forestier étranger (données)
[Termes descripteurs IGN] qualité des données
[Termes descripteurs IGN] variabilité
[Vedettes matières IGN] Inventaire forestierRésumé : (auteur) Aims : Plant responses to disturbances and environmental variation can manifest in communities as compositional nestedness (i.e., one community is a subset of another) and/or turnover (two communities represent different compositional gradient spaces). Yet, different sampling designs can artificially give an illusion of such compositional differences among two datasets, making it problematic to harmonize them in multi‐species analysis. We test the prediction that sampling differences which increase beta‐diversity components (nestedness and turnover) among two vegetation datasets will decrease their exchangeability.
Location : Boreal forests of Tanana River region, interior Alaska, USA.
Methods : We develop novel methods for comparing compositional variation among two datasets in nonmetric multidimensional scaling (NMDS) ordination. Resampled NMDS establishes internal sampling variability for each dataset independently, and reciprocal NMDS determines external exchangeability when the two are mutually exchanged. We first compare simulated data with specified beta‐diversity differences, then evaluate two forest inventories based on local vs regional sampling designs in Alaska's boreal forests.
Results : As simulated species turnover and nestedness increased, internal sampling variability remained essentially constant, but external exchangeability progressively declined. Species turnover (not nestedness) had the larger negative effect on exchangeability. Among the boreal forest inventories, internal sampling variability was relatively similar, and exchangeability was weakly moderate, but the regional inventory exhibited much better fit to broad‐scale environment. Species turnover (not nestedness) contributed the majority of beta‐diversity differences among the two forest inventories, suggesting that strong environmental gradients were unequally represented.
Conclusions : Species turnover alters multivariate outcomes more drastically than species nestedness. Therefore, combining two vegetation datasets may be inadvisable when turnover prevails. Instead, a multi‐scale perspective, with separate but complementary forest inventory analyses, can portray local and regional variation at appropriate scales. Our method is tractable for assessing exchangeability of potentially inconsistent sampling designs, like those that are common in synthesis studies and long‐term ecological monitoring.Numéro de notice : A2019-373 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1111/jvs.12694 date de publication en ligne : 07/11/2018 En ligne : https://doi.org/10.1111/jvs.12694 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93412
in Journal of vegetation science > vol 30 n° 1 (January 2019) . - pp 18 - 29[article]
Titre : Remote sensing of environmental changes in cold regions Type de document : Monographie Auteurs : Jinyang Du, Editeur scientifique ; Jennifer D. Watts, Editeur scientifique ; Hui Lu, Editeur scientifique ; et al., Editeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Collection : Remote sensing Importance : 210 p. ISBN/ISSN/EAN : 978-3-03921-571-3 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] Alaska (Etats-Unis)
[Termes descripteurs IGN] Arctique
[Termes descripteurs IGN] changement climatique
[Termes descripteurs IGN] climat froid
[Termes descripteurs IGN] cryosphère
[Termes descripteurs IGN] eau de surface
[Termes descripteurs IGN] extraction de la végétation
[Termes descripteurs IGN] image MODIS
[Termes descripteurs IGN] image radar moirée
[Termes descripteurs IGN] image Radarsat
[Termes descripteurs IGN] impact sur l'environnement
[Termes descripteurs IGN] incendie
[Termes descripteurs IGN] nadir
[Termes descripteurs IGN] neigeRésumé : (Editeur) This Special Issue gathers papers reporting recent advances in the remote sensing of cold regions. It includes contributions presenting improvements in modeling microwave emissions from snow, assessment of satellite-based sea ice concentration products, satellite monitoring of ice jam and glacier lake outburst floods, satellite mapping of snow depth and soil freeze/thaw states, near-nadir interferometric imaging of surface water bodies, and remote sensing-based assessment of high arctic lake environment and vegetation recovery from wildfire disturbances in Alaska. A comprehensive review is presented to summarize the achievements, challenges, and opportunities of cold land remote sensing. Note de contenu :
Modelling the L-Band Snow-Covered Surface Emission in a Winter Canadian Prairie Environment
Alexandre Roy, Marion Leduc-Leballeur, Ghislain Picard, Alain Royer, Peter Toose, Chris Derksen, Juha Lemmetyinen, Aaron Berg, Tracy Rowlandson and Mike Schwank
ComparisonofPassiveMicrowaveDatawithShipbornePhotographicObservationsofSummer Sea Ice Concentration along an Arctic Cruise Path
Qingkai Wang, Peng Lu, Yongheng Zu, Zhijun Li, Matti Leppa¨ranta and Guiyong Zhang
Radar Scatter Decomposition to Differentiate between Running Ice Accumulations and Intact Ice Covers along Rivers
Karl–Erich Lindenschmidt and Zhaoqin Li
Development of a Snow Depth Estimation Algorithm over China for the FY-3D/MWRI
Jianwei Yang, Lingmei Jiang, Shengli Wu, Gongxue Wang, Jian Wang and Xiaojing Liu
Development of a Parameterized Model to Estimate Microwave Radiation Response Depth of Frozen Soil
Tao Zhang, Lingmei Jiang, Shaojie Zhao, Linna Chai, Yunqing Li and Yuhao Pan
Mapping High Mountain Lakes Using Space-Borne Near-Nadir SAR Observations
Shengyang Li, Hong Tan, Zhiwen Liu, Zhuang Zhou, Yunfei Liu, Wanfeng Zhang, Kang Liu and Bangyong Qin
Development of Supraglacial Ponds in the Everest Region, Nepal, between 1989 and 2018
Mohan Bahadur Chand and Teiji Watanabe
Impacts of Climate Change and Intensive Lesser Snow Goose (Chen caerulescens caerulescens) Activity on Surface Water in High Arctic Pond Complexes
T. Kiyo F. Campbell, Trevor C. Lantz and Robert H. Fraser
Recovery Rates of Wetland Vegetation Greenness in Severely Burned Ecosystems of Alaska Derived from Satellite Image Analysis
Christopher PotterNuméro de notice : 26508 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03921-571-3 En ligne : https://doi.org/10.3390/books978-3-03921-571-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97134 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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Titre : Integrating SAR and derived products into operational volcano monitoring and decision support systems Type de document : Article/Communication Auteurs : Franz J. Meyer, Auteur ; D.B. McAlpin, Auteur ; W. Gong, Auteur ; et al., Auteur Année de publication : 2015 Article en page(s) : pp 106 - 117 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] Alaska (Etats-Unis)
[Termes descripteurs IGN] détection de changement
[Termes descripteurs IGN] éruption volcanique
[Termes descripteurs IGN] gestion des risques
[Termes descripteurs IGN] image radar moirée
[Termes descripteurs IGN] intégration de données
[Termes descripteurs IGN] séisme
[Termes descripteurs IGN] série temporelle
[Termes descripteurs IGN] surveillance géologique
[Termes descripteurs IGN] volcanRésumé : (auteur) Remote sensing plays a critical role in operational volcano monitoring due to the often remote locations of volcanic systems and the large spatial extent of potential eruption pre-cursor signals. Despite the all-weather capabilities of radar remote sensing and its high performance in monitoring of change, the contribution of radar data to operational monitoring activities has been limited in the past. This is largely due to: (1) the high costs associated with radar data; (2) traditionally slow data processing and delivery procedures; and (3) the limited temporal sampling provided by spaceborne radars. With this paper, we present new data processing and data integration techniques that mitigate some of these limitations and allow for a meaningful integration of radar data into operational volcano monitoring decision support systems. Specifically, we present fast data access procedures as well as new approaches to multi-track processing that improve near real-time data access and temporal sampling of volcanic systems with SAR data. We introduce phase-based (coherent) and amplitude-based (incoherent) change detection procedures that are able to extract dense time series of hazard information from these data. For a demonstration, we present an integration of our processing system with an operational volcano monitoring system that was developed for use by the Alaska Volcano Observatory (AVO). Through an application to a historic eruption, we show that the integration of SAR into systems such as AVO can significantly improve the ability of operational systems to detect eruptive precursors. Therefore, the developed technology is expected to improve operational hazard detection, alerting, and management capabilities. Numéro de notice : A2015-057 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern En ligne : http://www.sciencedirect.com/science/article/pii/S0924271614001270 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=75311
in ISPRS Journal of photogrammetry and remote sensing > vol 100 (February 2015) . - pp 106 - 117[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 081-2015021 RAB Revue Centre de documentation En réserve 3L Disponible 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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PermalinkMapping 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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PermalinkMarch2003 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)
PermalinkPermalinkDerivation of a threshold function for the advanced very high resolution radiometer 3, 75um channel and its application in automatic cloud discrimination over snow/ice surfaces / X. Xiong in International Journal of Remote Sensing IJRS, vol 25 n° 15 (August 2004)
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