Centre dedocumentation
scientifique

Constraint-based evaluation of map images generalized by deep learning / Azelle Courtial in Journal of Geovisualization and Spatial Analysis, vol 6 n° 1 (June 2022)  

Public [article]  inJournal of Geovisualization and Spatial Analysis > vol 6 n° 1 (June 2022) . - n° 13 Titre : Constraint-based evaluation of map images generalized by deep learning Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : n° 13 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond [Termes IGN] connexité (graphes) [Termes IGN] données d'entrainement (apprentissage automatique) [Termes IGN] montagne [Termes IGN] programmation par contraintes [Termes IGN] qualité des données [Termes IGN] rendu réaliste [Termes IGN] route [Vedettes matières IGN] Généralisation Résumé : (auteur) Deep learning techniques have recently been experimented for map generalization. Although promising, these experiments raise new problems regarding the evaluation of the output images. Traditional map generalization evaluation cannot directly be applied to the results in a raster format. Additionally, the internal evaluation used by deep learning models is mostly based on the realism of images and the accuracy of pixels, and none of these criteria is sufficient to evaluate a generalization process. Finally, deep learning processes tend to hide the causal mechanisms and do not always guarantee a result that follows cartographic principles. In this article, we propose a method to adapt constraint-based evaluation to the images generated by deep learning models. We focus on the use case of mountain road generalization, and detail seven raster-based constraints, namely, clutter, coalescence reduction, smoothness, position preservation, road connectivity preservation, noise absence, and color realism constraints. These constraints can contribute to current studies on deep learning-based map generalization, as they can help guide the learning process, compare different models, validate these models, and identify remaining problems in the output images. They can also be used to assess the quality of training examples. Numéro de notice : A2022-449 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s41651-022-00104-2 Date de publication en ligne : 07/05/2022 En ligne : http://dx.doi.org/10.1007/s41651-022-00104-2 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100646 [article]

Performance analysis of low-cost GNSS stations for structural health monitoring of civil engineering structures / Nicolas Manzini in Structure and Infrastructure Engineering, vol 18 n° 5 ([01/05/2022])  

Public [article]  inStructure and Infrastructure Engineering > vol 18 n° 5 [01/05/2022] . - pp 595 - 611 Titre : Performance analysis of low-cost GNSS stations for structural health monitoring of civil engineering structures Type de document : Article/Communication Auteurs : Nicolas Manzini, Auteur ; André Orcesi, Auteur ; Christian Thom , Auteur ; Marc-Antoine Brossault, Auteur ; Serge Botton , Auteur ; Miguel Ortiz, Auteur ; John Dumoulin, Auteur Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 595 - 611 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] auscultation d'ouvrage [Termes IGN] déformation d'édifice [Termes IGN] effet thermique [Termes IGN] pont [Termes IGN] RTKLIB [Termes IGN] surveillance d'ouvrage [Termes IGN] test de performance [Termes IGN] topométrie de précision Résumé : (auteur) Global Navigation Satellite Systems (GNSS) have been used in various monitoring applications for the past two decades, as one of the very few options to provide absolute positions in a global reference frame. However, high performance GNSS stations are expensive, and sometimes may be impractical because of their size, power consumption or software requirements. Thus, the use of low-cost GNSS stations for structural health monitoring (SHM) has gained increasing attention. This paper presents a detailed experimental assessment of multiple combinations of GNSS receivers and antennas, and highlights an optimal cost-efficient solution for monitoring applications. Several sets of processing parameters and constraints are also evaluated using open source RTKLib software. The performance of the proposed solution is evaluated through two experimental dynamic scenarios, proving its ability to track quick displacements down to 4 mm and oscillations of 1 cm with a frequency up to 0.25 Hz with a 1 Hz receiver. Finally, a two-week dataset acquired from on a network of low-cost GNSS stations deployed on a suspended bridge is used to validate on-site performance. Results show good agreement between GNSS time series, traditional displacement sensors, and numerical simulations made using an operational mechanical model of the bridge, highlighting the potential of such low-cost solutions for structural health monitoring applications. Numéro de notice : A2021-170 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15732479.2020.1849320 Date de publication en ligne : 30/11/2020 En ligne : https://doi.org/10.1080/15732479.2020.1849320 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97105 [article]

Comparison of atmospheric mass density models using a new data source: COSMIC satellite ephemerides / Yang Yang in IEEE Aerospace and Electronic Systems Magazine, vol 37 n° 2 (February 2022)  

Public [article]  inIEEE Aerospace and Electronic Systems Magazine > vol 37 n° 2 (February 2022) . - pp 6 - 22 Titre : Comparison of atmospheric mass density models using a new data source: COSMIC satellite ephemerides Type de document : Article/Communication Auteurs : Yang Yang, Auteur ; Ronald Maj, Auteur ; Changyong He , Auteur ; Robert Norman, Auteur ; Emma Kerr, Auteur ; Brett Anthony Carter, Auteur ; Julie Louise Currie, Auteur ; Steve Gower, Auteur Année de publication : 2022 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 6 - 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale [Termes IGN] analyse comparative [Termes IGN] atmosphère terrestre [Termes IGN] éphémérides de satellite [Termes IGN] International Reference Ionosphere [Termes IGN] masse d'air [Termes IGN] modèle atmosphérique [Termes IGN] orbite basse [Termes IGN] teneur totale en électrons Résumé : (auteur) Atmospheric mass density (AMD) plays a vital role in the drag calculation for space objects in low Earth orbit. Many empirical AMD models have been developed and used for orbit prediction and efforts continue to improve their accuracy in forecasting high-altitude atmospheric conditions. Previous studies have assessed these models at the height of 200 km to 600 km. In this paper, four state-of-the-art AMD models, i.e., MSISE90, MSISE00, JB2008 and DTM2013 are assessed for their orbit prediction (OP) capabilities by using a new data source of COSMIC satellite ephemerides at an orbital height of ~800 km, where the contribution of ions in the total AMD is more significant. A new testing model was developed by accounting for ion contribution based on the International Reference Ionosphere 2016 model, including many more ion species that are not accounted for in other AMD models. In the assessment, two periods of forty days were chosen in 2014-2015 and 2018-2019, representing solar maximum and minimum periods, respectively, to assess four existing AMD models and the proposed model. Thorough analyses were conducted to compare OP results using different AMD models with precise reference ephemerides of COSMIC satellites and based on various space weather indices. It is shown that the proposed model outperforms all other AMD models in terms of OP errors during the solar maximum period. During solar minimum, the drag acceleration is relatively small for COSMIC satellites. Assessment of all AMD models in the orbit prediction process tends to be contaminated by the remaining uncertainty sources, such as solar radiation pressure. Numéro de notice : A2022-070 Affiliation des auteurs : ENSG+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/MAES.2021.3125101 Date de publication en ligne : 20/12/2021 En ligne : https://doi.org/10.1109/MAES.2021.3125101 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99376 [article]

Voir aussi

• Comparison of atmospheric mass density models using a new data source: COSMIC satellite ephemerides / Yang Yang (2020)  

Proceedings of the 1st Conference of the European Association on Quality Control of Bridges and Structures : EUROSTRUCT 2021. An automated machine learning-based approach for structural novelty detection based on SHM / Nicolas Manzini (2022)  

Public Titre de série : Proceedings of the 1st Conference of the European Association on Quality Control of Bridges and Structures : EUROSTRUCT 2021 Titre : An automated machine learning-based approach for structural novelty detection based on SHM Type de document : Article/Communication Auteurs : Nicolas Manzini, Auteur ; Ndeye Mar, Auteur ; Franziska Schmidt, Auteur ; Jean-François Bercher, Auteur ; André Orcesi, Auteur ; Pierre Marchand, Auteur ; Julien Gazeaux , Auteur ; Christian Thom , Auteur Editeur : Springer Nature Année de publication : 2022 Collection : Lecture Notes in Civil Engineering num. 200 Projets : 2-Pas d'info accessible - article non ouvert / Importance : pp 1180 - 1189 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale [Termes IGN] apprentissage automatique [Termes IGN] détection d'anomalie [Termes IGN] ouvrage d'art [Termes IGN] pont [Termes IGN] régression multiple [Termes IGN] réseau de capteurs [Termes IGN] résidu [Termes IGN] surveillance d'ouvrage Résumé : (auteur) One major goal of structural health monitoring (SHM) is to detect, and possibly locate, quantify or predict damage on structures. Without detailed knowledge of structural mechanical behavior, data analysis is a complex task and operational monitoring is often limited to the use of more or less arbitrary thresholds. Data-driven techniques, which rely on a statistical analysis of data, have encountered a growing interest over the past two decades. In parallel, SHM is now increasingly considered for several types of structures with the development of low-cost sensors and IoT. In this context, this paper proposes an approach based on multiple automated machine learning-based models for novelty detection and location in monitoring data. This study focuses on the monitoring of large structures with multiple sensors. For each sensor, multiple regression models (based on neural networks) are generated using the same training set, with various input data: internal temperature, environmental conditions, or data from other sensors deployed on the structure. Anomalies are then identified in the dataset based on residuals between model outputs and in situ data. For a given sensor, residuals of all models are then compiled to produce an anomaly indicator. This paper presents some of the results obtained on data acquired from the monitoring of a large concrete bridge. Some anomalies are simulated and added to the dataset to demonstrate the detection performance of the proposed approach. Numéro de notice : C2022-001 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : POSITIONNEMENT Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1007/978-3-030-91877-4_134 Date de publication en ligne : 12/12/2021 En ligne : https://doi.org/10.1007/978-3-030-91877-4_134 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99378

The Loop Effect: how climate change impacts the mitigation potential of the French forest sector / Philippe Delacote in Journal of Forest Economics, vol 36 n° 3 ([01/06/2021])  

Public [article]  inJournal of Forest Economics > vol 36 n° 3 [01/06/2021] . - pp 201 - 264 Titre : The Loop Effect: how climate change impacts the mitigation potential of the French forest sector Type de document : Article/Communication Auteurs : Philippe Delacote, Auteur ; Antonello Lobianco, Auteur ; Sylvain Caurla, Auteur ; Jean-Daniel Bontemps , Auteur ; Anna Lungarska, Auteur ; Pierre Mérian , Auteur ; Miguel Rivière, Auteur ; Ahmed Barkaoui, Auteur Année de publication : 2021 Projets : 2-Pas d'info accessible - article non ouvert / Article en page(s) : pp 201 - 264 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] changement climatique [Termes IGN] dioxyde de carbone [Termes IGN] économie forestière [Termes IGN] industrie forestière [Termes IGN] modèle numérique [Vedettes matières IGN] Economie forestière Résumé : (auteur) Objectives: Evaluate the capacity of temperate forest resources to both provide climate change mitigation and to sustain the downstream timber sector explicitly considering the cascade of biophysical and economic drivers (in particular, climate change impacts and subsequent adaptation actions) and their uncertainty. Methodology: A recursive bio-economic model of French forest resources, management, and timber markets has been coupled for this study with spatial statistical models of forest response to climate change long-term scenarios and land-use change. Main Results: (a) Climate change impacts on tree mortality are greater than those on tree growth variations; (b) Due to increasing competition with agriculture, climate change may reverse current trends in forest area expansion; (c) Due to rising average tree sizes, volume growth strongly declines over time and may eventually cease within the next century; (d) Future climate change impacts already have strong consequences on today’s forest investment profitability; (e) The relative importance of forest substitution over forest sequestration increases as the timeframe increases; (f) While the forest sector has the potential to counterbalance a significant share of the national carbon emissions, this potential is threatened by climate change and the need to adapt to it. Profit-driven forest management does increase mitigation; (g) Uncertainty derived from using different climatic models over the same IPCC storyline has the same order of magnitude as the uncertainty derived from using the same climatic model under different storylines. Numéro de notice : A2021-062 Affiliation des auteurs : LIF+Ext (2020- ) Thématique : FORET Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1561/112.00000522 En ligne : http://dx.doi.org/10.1561/112.00000522 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96699 [article]

A data fusion-based framework to integrate multi-source VGI in an authoritative land use database / Lanfa Liu in International Journal of Digital Earth, vol 14 n° 4 (April 2021)  

Permalink

Search for top‐down and bottom‐up drivers of latitudinal trends in insect herbivory in oak trees in Europe / Elena Valdés-Correcher in Global ecology and biogeography, vol 30 n° 3 (March 2021)  

Permalink

Assessing the interest of a multi-modal gap-filling strategy for monitoring changes in grassland parcels / Anatol Garioud (2021)  

Permalink

Assessment of sky diffuse irradiance and building reflected irradiance in cast shadows / Manchun Lei (2021)  

Permalink

Contextual land-cover map translation with semantic segmentation / Luc Baudoux (2021)  

Permalink

Diurnal cycles of C-band temporal coherence and backscattering coefficient over an olive orchard in a semi-arid area: Comparison of in situ and Sentinel-1 radar observations / Adnane Chakir (2021)  

Permalink

Diurnal cycles of C-band temporal coherence and backscattering coefficient over a wheat field in a semi-arid area / Nadia Ouaadi (2021)  

Permalink

Flex-ER: A platform to evaluate interaction techniques for immersive visualizations / María-Jesús Lobo in Proceedings of the ACM on Human-Computer Interaction, Vol 4 (November 2020)  

Permalink

Improving the accuracy of land cover classification in cloud persistent areas using optical and radar satellite image time series / Maylis Lopes in Methods in ecology and evolution, vol 11 n° 4 (April 2020)  

Permalink

ITRF2014, Earth figure changes, and geocenter velocity: Implications for GIA and recent ice melting / Laurent Métivier in Journal of geophysical research : Solid Earth, vol 125 n° 2 (February 2020)  

Permalink