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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)  

Public [article]  inJournal of vegetation science > vol 30 n° 1 (January 2019) . - pp 18 - 29 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 IGN] Alaska (Etats-Unis) [Termes IGN] forêt boréale [Termes IGN] inventaire forestier (techniques et méthodes) [Termes IGN] inventaire forestier étranger (données) [Termes IGN] qualité des données [Termes IGN] variabilité [Vedettes matières IGN] Inventaire forestier Résumé : (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 [article]

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

Public 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 ; Lingmei Jiang, Editeur scientifique ; Paolo Tarolli, Editeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 210 p. ISBN/ISSN/EAN : 978-3-03921-571-3 Note générale : Bibliographie This book is a printed edition of the Special Issue Remote sensing of environmental changes in cold regions that was published in Remote Sensing Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Alaska (Etats-Unis) [Termes IGN] Arctique [Termes IGN] changement climatique [Termes IGN] climat froid [Termes IGN] cryosphère [Termes IGN] eau de surface [Termes IGN] extraction de la végétation [Termes IGN] image Aqua-MODIS [Termes IGN] image radar moirée [Termes IGN] image Radarsat [Termes IGN] image Terra-MODIS [Termes IGN] impact sur l'environnement [Termes IGN] incendie [Termes IGN] nadir [Termes IGN] neige Résumé : (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 - Comparison of Passive Microwave Data with Shipborne Photographic Observation sof Summer 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 Potter Numéro 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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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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Bases de données ethnographiques / Françoise de Blomac in SIG la lettre, n° 76 (avril 2006)

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Derivation 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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