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Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network / Nantheera Anantrasirichai in IEEE Transactions on geoscience and remote sensing, vol 59 n° 4 (April 2021)  

Public [article]  inIEEE Transactions on geoscience and remote sensing > vol 59 n° 4 (April 2021) . - pp 2940 - 2950 Titre : Detecting ground deformation in the built environment using sparse satellite InSAR data with a convolutional neural network Type de document : Article/Communication Auteurs : Nantheera Anantrasirichai, Auteur ; Juliet Biggs, Auteur ; Krisztina Kelevitz, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 2940 - 2950 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image radar et applications [Termes IGN] apprentissage automatique [Termes IGN] bati [Termes IGN] classification par réseau neuronal convolutif [Termes IGN] covariance [Termes IGN] déformation de la croute terrestre [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] effet atmosphérique [Termes IGN] image radar moirée [Termes IGN] interféromètrie par radar à antenne synthétique [Termes IGN] interpolation spatiale [Termes IGN] matrice [Termes IGN] optimisation (mathématiques) [Termes IGN] représentation parcimonieuse [Termes IGN] Royaume-Uni [Termes IGN] zone urbaine Résumé : (auteur) The large volumes of Sentinel-1 data produced over Europe are being used to develop pan-national ground motion services. However, simple analysis techniques like thresholding cannot detect and classify complex deformation signals reliably making providing usable information to a broad range of nonexpert stakeholders a challenge. Here, we explore the applicability of deep learning approaches by adapting a pretrained convolutional neural network (CNN) to detect deformation in a national-scale velocity field. For our proof-of-concept, we focus on the U.K. where previously identified deformation is associated with coal-mining, ground water withdrawal, landslides, and tunneling. The sparsity of measurement points and the presence of spike noise make this a challenging application for deep learning networks, which involve calculations of the spatial convolution between images. Moreover, insufficient ground truth data exist to construct a balanced training data set, and the deformation signals are slower and more localized than in previous applications. We propose three enhancement methods to tackle these problems: 1) spatial interpolation with modified matrix completion; 2) a synthetic training data set based on the characteristics of the real U.K. velocity map; and 3) enhanced overwrapping techniques. Using velocity maps spanning 2015–2019, our framework detects several areas of coal mining subsidence, uplift due to dewatering, slate quarries, landslides, and tunnel engineering works. The results demonstrate the potential applicability of the proposed framework to the development of automated ground motion analysis systems. Numéro de notice : A2021-283 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12518-020-00323-6 Date de publication en ligne : 31/08/2020 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=97391 [article]

Remote sensing analysis of small scale dynamic phenomena in the atmospheric boundary layer / Kostas Cheliotis (2021)  

Public Titre : Remote sensing analysis of small scale dynamic phenomena in the atmospheric boundary layer Type de document : Thèse/HDR Auteurs : Kostas Cheliotis, Auteur ; Hervé Delbarre, Auteur Editeur : Dunkerque : Université du Littoral-Côte-d'Opale Année de publication : 2021 Importance : 139 p. Format : 21 x 30 cm Note générale : bibliographie Thèse présentée pour obtenir le grade de Docteur de l’Université du Littoral Côte d’Opale, Mention : Physique, Spécialité : Milieux dilués et optiques fondamentales Langues : Français (fre) Descripteur : [Vedettes matières IGN] Atmosphère [Termes IGN] analyse discriminante [Termes IGN] analyse texturale [Termes IGN] balayage laser [Termes IGN] classification dirigée [Termes IGN] données lidar [Termes IGN] données localisées 3D [Termes IGN] effet atmosphérique [Termes IGN] lidar à effet Doppler [Termes IGN] lidar atmosphérique [Termes IGN] météorologie [Termes IGN] vent Index. décimale : THESE Thèses et HDR Résumé : (auteur) The aim of this thesis project was to study the coherent turbulent structures (convective rolls & streaks) and more generally the medium to large fluctuations in the atmospheric boundary layer using the observations recorded by a single Doppler (wind) lidar during a 2-month campaign in Paris, France. An innovative method was developed in order to classify automatically the radial wind speed patterns visible on the quasi-horizontal lidar scans, based on texture analysis parameters and supervised machine learning algorithms. A 150-case training ensemble was built using ancillary data (satellite pictures and weather observations) to ascertain the manual classification into four types: rolls, thermals, streaks and “others”. The performance of the classification process was assessed on the training ensemble using the 10-fold cross-validation method. A very satisfying 9% error was obtained for the Quadratic Discriminant Analysis algorithm, using only 5 texture analysis parameters classifiers. This process was then applied to classify the whole dataset (4577 lidar scans) and the results showed that the classified structures respected a plausible diurnal cycle and were associated with the meteorological parameters as expected by the theoretical knowledge. The size of the coherent structures in the direction transverse to the mean wind were estimated from the wind spectrums on a four-day case study. They ranged from 400 to 800 m for the cases classified as streaks, and from 1.3 to 2.0 km for the cases classified as rolls. These results pave the way for future long-term studies providing statistical insight on the frequency of occurrence of the different structure types, their physical properties, and their impact on pollutants’ concentrations. Numéro de notice : 28616 Affiliation des auteurs : non IGN Nature : Thèse française Note de thèse : Thèse de Doctorat : Milieux dilués et optiques fondamentales : Côte d'Opale : France : 2021 Organisme de stage : Laboratoire de Physico-Chimie de l'Atmosphère DOI : sans En ligne : https://hal.science/tel-03259369/ Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99504

Single image dehazing via an improved atmospheric scattering model / Mingye Ju in The Visual Computer, vol 33 n° 12 (December 2017)  

Public [article]  inThe Visual Computer > vol 33 n° 12 (December 2017) . - pp 1613 - 1625 Titre : Single image dehazing via an improved atmospheric scattering model Type de document : Article/Communication Auteurs : Mingye Ju, Auteur ; Dengyin Zhang, Auteur ; Xuemei Wang, Auteur Année de publication : 2017 Article en page(s) : pp 1613 - 1625 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] brouillard [Termes IGN] diffusion du rayonnement [Termes IGN] effet atmosphérique [Termes IGN] image isolée [Termes IGN] scène urbaine [Termes IGN] segmentation d'image Résumé : (Auteur) Under foggy or hazy weather conditions, the visibility and color fidelity of outdoor images are prone to degradation. Hazy images can be the cause of serious errors in many computer vision systems. Consequently, image haze removal has practical significance for real-world applications. In this study, we first analyze the inherent weaknesses of the atmospheric scattering model and propose an improvement to address those weaknesses. Then, we present a fast image haze removal algorithm based on the improved model. In our proposed method, the input image is partitioned into several scenes based on the haze thickness. Next, averaging and erosion operations calculate the rough scene luminance map in a scene-wise manner. We obtain the rough scene transmission map by maximizing the contrast in each scene and then develop a way to gently remove the haze using an adaptive method for adjusting scene transmission based on scene features. In addition, we propose a guided total variation model for edge optimization, so as to prevent from the block effect as well as to eliminate the negative effect from the wrong scene segmentation results. The experimental results demonstrate that our method is effective in solving a series of common problems, including uneven illuminance, overenhanced and oversaturated images, and so forth. Moreover, our method outperforms most current dehazing algorithms in terms of visual effects, universality, and processing speed. Numéro de notice : A2017-715 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Article DOI : 10.1007/s00371-016-1305-1 En ligne : https://doi.org/10.1007/s00371-016-1305-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=88099 [article]

Assessment of second- and third-order ionospheric effects on regional networks : case study in China with longer CMONOC GPS coordinate time series / Liansheng Deng in Journal of geodesy, vol 91 n° 2 (February 2017)  

Public [article]  inJournal of geodesy > vol 91 n° 2 (February 2017) . - pp 207 - 227 Titre : Assessment of second- and third-order ionospheric effects on regional networks : case study in China with longer CMONOC GPS coordinate time series Type de document : Article/Communication Auteurs : Liansheng Deng, Auteur ; Weiping Jiang, Auteur ; Zhao Li, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 207 - 227 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Systèmes de référence et réseaux [Termes IGN] analyse diachronique [Termes IGN] Chine [Termes IGN] coordonnées GPS [Termes IGN] correction ionosphérique [Termes IGN] déformation de la croute terrestre [Termes IGN] effet atmosphérique [Termes IGN] propagation ionosphérique [Termes IGN] réseau géodésique local [Termes IGN] retard ionosphèrique [Termes IGN] série temporelle [Termes IGN] surcharge atmosphérique Résumé : (Auteur) Higher-order ionospheric (HOI) delays are one of the principal technique-specific error sources in precise global positioning system analysis and have been proposed to become a standard part of precise GPS data processing. In this research, we apply HOI delay corrections to the Crustal Movement Observation Network of China’s (CMONOC) data processing (from January 2000 to December 2013) and furnish quantitative results for the effects of HOI on CMONOC coordinate time series. The results for both a regional reference frame and global reference frame are analyzed and compared to clarify the HOI effects on the CMONOC network. We find that HOI corrections can effectively reduce the semi-annual signals in the northern and vertical components. For sites with lower semi-annual amplitudes, the average decrease in magnitude can reach 30 and 10 % for the northern and vertical components, respectively. The noise amplitudes with HOI corrections and those without HOI corrections are not significantly different. Generally, the HOI effects on CMONOC networks in a global reference frame are less obvious than the results in the regional reference frame, probably because the HOI-induced errors are smaller in comparison to the higher noise levels seen when using a global reference frame. Furthermore, we investigate the combined contributions of environmental loading and HOI effects on the CMONOC stations. The largest loading effects on the vertical displacement are found in the mid- to high-latitude areas. The weighted root mean square differences between the corrected and original weekly GPS height time series of the loading model indicate that the mass loading adequately reduced the scatter on the CMONOC height time series, whereas the results in the global reference frame showed better agreements between the GPS coordinate time series and the environmental loading. When combining the effects of environmental loading and HOI corrections, the results with the HOI corrections reduced the scatter on the observed GPS height coordinates better than the height when estimated without HOI corrections, and the combined solutions in the regional reference frame indicate more preferred improvements. Therefore, regional reference frames are recommended to investigate the HOI effects on regional networks. Numéro de notice : A2017-064 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0957-y En ligne : http://dx.doi.org/10.1007/s00190-016-0957-y Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84278 [article]

Improved ambiguity resolution for URTK with dynamic atmosphere constraints / Weiming Tang in Journal of geodesy, vol 90 n° 12 (December 2016)  

Public [article]  inJournal of geodesy > vol 90 n° 12 (December 2016) . - pp 1359 - 1369 Titre : Improved ambiguity resolution for URTK with dynamic atmosphere constraints Type de document : Article/Communication Auteurs : Weiming Tang, Auteur ; Wenjian Liu, Auteur ; Xuan Zou, Auteur ; et al., Auteur Année de publication : 2016 Article en page(s) : pp 1359 - 1369 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Navigation et positionnement [Termes IGN] correction ionosphérique [Termes IGN] effet atmosphérique [Termes IGN] positionnement cinématique en temps réel [Termes IGN] précision du positionnement [Termes IGN] résidu [Termes IGN] résolution d'ambiguïté Résumé : (Auteur) Raw observation processing method with prior knowledge of ionospheric delay could strengthen the ambiguity resolution (AR), but it does not make full use of the relatively longer wavelength of wide-lane (WL) observation. Furthermore, the accuracy of calculated atmospheric delays from the regional augmentation information has quite different in quality, while the atmospheric constraint used in the current methods is usually set to an empirical value. A proper constraint, which matches the accuracy of calculated atmospheric delays, can most effectively compensate the residual systematic biases caused by large inter-station distances. Therefore, the standard deviation of the residual atmospheric parameters should be fine-tuned. This paper presents an atmosphere-constrained AR method for undifferenced network RTK (URTK) rover, whose ambiguities are sequentially fixed according to their wavelengths. Furthermore, this research systematically analyzes the residual atmospheric error and finds that it mainly varies along the positional relationship between the rover and the chosen reference stations. More importantly, its ionospheric part of certain location will also be cyclically influenced every day. Therefore, the standard deviation of residual ionospheric error can be modeled by a daily repeated cosine or other functions with the help of data one day before, and applied by rovers as pseudo-observation. With the data collected at 29 stations from a continuously operating reference station network in Guangdong Province (GDCORS) in China, the efficiency of the proposed approach is confirmed by improving the success and error rates of AR for 10-20 % compared to that of the WL-L1-IF one, as well as making much better positioning accuracy. Numéro de notice : A2016-807 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0928-3 En ligne : http://dx.doi.org/10.1007/s00190-016-0928-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82595 [article]

Monitoring and prediction of precipitable water vapor using GPS data in Turkey / Kutubuddin Ansari in Journal of applied geodesy, vol 10 n° 4 (December 2016)  

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A global study of NDVI difference among moderate-resolution satellite sensors / Xingwang Fan in ISPRS Journal of photogrammetry and remote sensing, vol 121 (November 2016)  

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Variance components estimation of residual errors in GPS precise positioning / Darko Anđić in Geodetski vestnik, vol 60 n° 3 (September - November 2016)  

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A synergy method to improve ensemble weather predictions and differential SAR interferograms / Franz-Georg Ulmer in ISPRS Journal of photogrammetry and remote sensing, vol 109 (November 2015)  

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Assessment of observing time-variable gravity from GOCE GPS and accelerometer observations / Pieter N.A.M. Visser in Journal of geodesy, vol 88 n° 11 (November 2014)  

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La forêt française, l'agroforesterie et la filière bois : quel potentiel d'atténuation climatique à moyen et long terme ? / Michel de Galbert in Revue forestière française, vol 66 n° 5 (septembre - octobre 2014)  

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Remote sensing imagery / Florence Tupin (2014)  

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Improved topographic mapping through high-resolution SAR interferometry with atmospheric effect removal / Mingsheng Liao in ISPRS Journal of photogrammetry and remote sensing, vol 80 (June 2013)  

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Evaluation of different methods to retrieve the hemispherical downwelling irradiance in the thermal infrared region for field measurements / Vicente Garcia-Santos in IEEE Transactions on geoscience and remote sensing, vol 51 n° 4 Tome 2 (April 2013)  

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Remote sensing of seasonal variability of fractional vegetation cover and its object-based spatial pattern analysis over mountain areas / Guijun Yang in ISPRS Journal of photogrammetry and remote sensing, vol 77 (March 2013)  

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