Publications du LaSTIG
Les publications antérieures au LaSTIG sont celles des laboratoires qui ont formé le LaSTIG : COGIT, LOEMI et MATIS, à l'exception du LAREG - Vous pouvez affiner la recherche au sein des références
![](./images/expand_all.gif)
![](./images/collapse_all.gif)
![Imprimer...](./images/print.gif)
City-descriptive input data for urban climate models: Model requirements, data sources and challenges / Valéry Masson in Urban climate, vol 31 (March 2020)
![]()
[article]
Titre : City-descriptive input data for urban climate models: Model requirements, data sources and challenges Type de document : Article/Communication Auteurs : Valéry Masson, Auteur ; Wieke Heldens, Auteur ; Erwan Bocher, Auteur ; Marion Bonhomme, Auteur ; Bénédicte Bucher , Auteur ; et al., Auteur
Année de publication : 2020 Projets : URCLIM / Masson, Valéry Article en page(s) : n° 100536 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] arbre urbain
[Termes IGN] données localisées numériques
[Termes IGN] données socio-économiques
[Termes IGN] flore urbaine
[Termes IGN] morphologie urbaine
[Termes IGN] occupation du sol
[Termes IGN] ville
[Termes IGN] zone urbaineRésumé : (auteur) Cities are particularly vulnerable to meteorological hazards because of the concentration of population, goods, capital stock and infrastructure. Urban climate services require multi-disciplinary and multi-sectorial approaches and new paradigms in urban climate modelling. This paper classifies the required urban input data for both mesoscale state-of-the-art Urban Canopy Models (UCMs) and microscale Obstacle Resolving Models (ORM) into five categories and reviews the ways in which they can be obtained. The first two categories are (1) land cover, and (2) building morphology. These govern the main interactions between the city and the urban climate and the Urban Heat Island. Interdependence between morphological parameters and UCM geometric hypotheses are discussed. Building height, plan and wall area densities are recommended as the main input variables for UCMs, whereas ORMs require 3D building data. Recently, three other categories of urban data became relevant for finer urban studies and adaptation to climate change: (3) building design and architecture, (4) building use, anthropogenic heat and socio-economic data, and (5) urban vegetation data. Several methods for acquiring spatial information are reviewed, including remote sensing, geographic information system (GIS) processing from administrative cadasters, expert knowledge and crowdsourcing. Data availability, data harmonization, costs/efficiency trade-offs and future challenges are then discussed. Numéro de notice : A2020-003 Affiliation des auteurs : LASTIG+Ext (2016-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.uclim.2019.100536 Date de publication en ligne : 19/11/2019 En ligne : https://doi.org/10.1016/j.uclim.2019.100536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94290
in Urban climate > vol 31 (March 2020) . - n° 100536[article]Classification of time series of Sentinel-2 images for large scale mapping in Cameroon / Hermann Tagne (2020)
![]()
Titre : Classification of time series of Sentinel-2 images for large scale mapping in Cameroon Type de document : Article/Communication Auteurs : Hermann Tagne, Auteur ; Arnaud Le Bris , Auteur ; David Monkam, Auteur ; Clément Mallet
, Auteur
Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2020 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B3 Projets : TOSCA Parcelle / Le Bris, Arnaud Conférence : ISPRS 2020, Commission 3, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Archives Commission 3 Importance : pp 633 - 640 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] Cameroun
[Termes IGN] carte d'occupation du sol
[Termes IGN] classification
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] mise à jour de base de données
[Termes IGN] série temporelleRésumé : (auteur) Sentinel-2 satellites provide dense image time series exhibiting high spectral, spatial and temporal resolution. These images are in particular of utter interest to map Land-Cover (LC) at large scale. LC maps can now be computed on a yearly basis at the scale of a country with efficient supervised classifiers, assuming suitable training data are available. However, the efficient exploitation of large amount of Sentinel-2 imagery still remain challenging on unexplored areas where state-of-the-art classifiers are prone to fail. This paper focuses on Land-Cover mapping over Cameroon for the purpose of updating the national topographic geodatabase. The ι2 framework is adopted and tested for the specificity of the country. Here, experiments focus on generic classes (five) which enables providing robust focusing masks for higher resolution classifications. Two strategies are compared: (i) a LC map is calculated out of a year long time series and (ii) monthly LC maps are generated and merged into a single yearly map. Satisfactory accuracy scores are obtained, allowing to provide a first step towards finer-grained map retrieval. Numéro de notice : C2020-006 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B3-2020-633-2020 Date de publication en ligne : 21/08/2020 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B3-2020-633-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95656 CNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: first experiments / Arnaud Le Bris in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)
![]()
[article]
Titre : CNN semantic segmentation to retrieve past land cover out of historical orthoimages and DSM: first experiments Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; Sébastien Giordano
, Auteur ; Clément Mallet
, Auteur
Année de publication : 2020 Projets : HIATUS / Giordano, Sébastien Conférence : ISPRS 2020, Commission 2, virtual Congress, Imaging today foreseeing tomorrow 31/08/2020 02/09/2020 Nice (en ligne) France Annals Commission 2 Article en page(s) : pp 1013 - 1019 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] base de données historiques
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] image aérienne
[Termes IGN] modèle numérique de surface
[Termes IGN] occupation du sol
[Termes IGN] orthoimage
[Termes IGN] segmentation sémantiqueRésumé : (auteur) Images from archival aerial photogrammetric surveys are a unique and relatively unexplored means to chronicle 3D land-cover changes occurred since the mid 20th century. They provide a relatively dense temporal sampling of the territories with a very high spatial resolution. Thus, they offer time series data which can answer a large variety of long-term environmental monitoring studies. Besides, they are generally stereoscopic surveys, making it possible to derive 3D information (Digital Surface Models). In recent years, they have often been digitized, making them more suitable to be considered in automatic analyses processes. Some photogrammetric softwares make it possible to retrieve their geometry (pose and camera calibration) and to generate corresponding DSM and orthophotomosaic. Thus, archival aerial photogrammetric surveys appear as being a powerful remote sensing data source to study land use/cover evolution over the last century. However, several difficulties have to be faced to be able to use them in automatic analysis processes. Indeed, surveys available on a study area can exhibit very different characteristics: survey pattern, focal, spatial resolution, modality (panchromatic, colour, infrared…). Planimetric and altimetric accuracies of derived products strongly depend on these characteristics. Thus, analysis processes have to cope with these uncertainties. Another important gap states in the lack of training data. Deep learning methods and especially Convolutional Neural Networks (CNN) are at present the most efficient semantic segmentation methods as long as a sufficient training dataset is available. However, temporal gaps can be very important between existing available databases and archival data. In this study, two custom variants of simple yet effective U-net - Deconv-Net inspired DL architectures are developed to process ortho-image and DSM based information. They are then trained out of a groundtruth derived out of a recent database to process archival datasets. Numéro de notice : A2020-469 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : vers HAL Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-2-2020-1013-2020 Date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-1013-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95637
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-2-2020 (August 2020) . - pp 1013 - 1019[article]
Titre : Co-visualization of air temperature and urban data for visual exploration Type de document : Article/Communication Auteurs : Jacques Gautier , Auteur ; Mathieu Brédif
, Auteur ; Sidonie Christophe
, Auteur
Editeur : New-York : IEEE Computer society Année de publication : 2020 Projets : URCLIM / Masson, Valéry Conférence : IEEE VIS 2020, (VAST, INFOVIS, SCIVIS), premier forum for advances in visualization and visual analytics 25/10/2020 30/10/2020 en ligne France vers VIS.org Importance : 5 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] analyse géovisuelle
[Termes IGN] distribution spatiale
[Termes IGN] exploration de données géographiques
[Termes IGN] ilot thermique urbain
[Termes IGN] modèle 3D de l'espace urbain
[Termes IGN] morphologie urbaine
[Termes IGN] rendu (géovisualisation)
[Termes IGN] représentation graphique
[Termes IGN] température de l'air
[Termes IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Urban climate data remain complex to analyze regarding their spatial distribution. The co-visualization of simulated air temperature into urban models could help experts to analyze horizontal and vertical spatial distributions. We design a co-visualization framework enabling simulated air temperature data exploration, based on the graphic representation of three types of geometric proxies, and their co-visualization with a 3D urban model with various possible rendering styles. Through this framework, we aim at allowing meteorological researchers to visually analyze and interpret the relationships between simulated air temperature data and urban morphology. Numéro de notice : C2020-005 Affiliation des auteurs : UGE-LASTIG (2020- ) Autre URL associée : VIS 2020 Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/VIS47514.2020.00021 Date de publication en ligne : 01/02/2021 En ligne : https://doi.org/10.1109/VIS47514.2020.00021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96161 Documents numériques
en open access
Co-visualization... - pdf auteur -Adobe Acrobat PDFCoastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) / Yawo Konko in Advances in Remote Sensing, vol 9 n° 2 (June 2020)
![]()
[article]
Titre : Coastline change modelling induced by climate change using geospatial techniques in Togo (West Africa) Type de document : Article/Communication Auteurs : Yawo Konko, Auteur ; Appollonia Okhimambe, Auteur ; Pouwèréou Nimon, Auteur ; Jerry Asaana, Auteur ; Jean-Paul Rudant , Auteur ; Kouami Kokou, Auteur
Année de publication : 2020 Projets : 1-Pas de projet / Masson, Valéry Article en page(s) : pp 85 - 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] changement climatique
[Termes IGN] classification non dirigée
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données multisources
[Termes IGN] érosion côtière
[Termes IGN] image Landsat-ETM+
[Termes IGN] image Sentinel-MSI
[Termes IGN] niveau de la mer
[Termes IGN] Normalized Difference Water Index
[Termes IGN] outil d'aide à la décision
[Termes IGN] régression linéaire
[Termes IGN] série temporelle
[Termes IGN] surveillance du littoral
[Termes IGN] Togo
[Termes IGN] trait de côteRésumé : (auteur) Climate change is a major concern of humanity. One of the consequences of climate change is global warming causing melting glaciers, rising sea levels and shoreline regression. In Togo, the regression of shoreline leads to coastal erosion with significant damage on socio-economic infrastructures and human habitats. This research, basing on geospatial techniques, focuses on coastal erosion monitoring from 1988 to 2018 in Togo. It is interested in the extraction of shoreline and in the analysis of change. Various satellite images indexes have been developed for shoreline extraction but the major scientific problem concerns the precision of the different classification algorithms methods used for the extraction of the shoreline from these water index. This study used NDWI index from multisource satellite images. It assesses the performance of Otsu threshold segmentation, Iso Cluster Unsupervised Classification and Support Vector Machine (SVM) Supervised Classification methods for the extraction of the shoreline on NDWI index. The topographic morphology such as linear and non-linear coastal surfaces have been considered. The estimation of the rates of change of the shoreline was performed using the statistical linear regression method (LRR). The results revealed that the SVM Supervised Classification method showed good performance on linear and non-linear coastal surface than the other methods. For the kinematics of the shoreline, the southwest of the Togolese coast has an average erosion rate ranging from 2.49 to 5.07 m per year. The results obtained will serve as decision-making support tools for the design and implementation of appropriate adaptations plans to avoid the immersion of the asphalt road by sea, displacement of population and disturbance of human habitats. Numéro de notice : A2020-795 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.4236/ars.2020.92005 Date de publication en ligne : 08/06/2020 En ligne : https://doi.org/10.4236/ars.2020.92005 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96622
in Advances in Remote Sensing > vol 9 n° 2 (June 2020) . - pp 85 - 100[article]Collaborative user oriented metadata production on EuroSDR Geometadatalabs platform [paper and diaporama] / Bénédicte Bucher (2020)
![]()
PermalinkCombining optical and radar satellite image time series to map natural vegetation: savannas as an example / Maylis Lopes in Remote sensing in ecology and conservation, vol 6 n° 3 (September 2020)
PermalinkComparing supervised learning algorithms for Spatial Nominal Entity recognition / Amine Medad (2020)
PermalinkComplex deformation at shallow depth during the 30 October 2016 Mw6.5 Norcia earthquake: interferencebetween tectonic and gravity processes? / Arthur Delorme in Tectonics, vol 39 n° 2 (February 2020)
![]()
PermalinkConciliating perspectives from mapping agencies and web of data on successful European SDIs: toward a European geographic knowledge graph / Bénédicte Bucher in ISPRS International journal of geo-information, vol 9 n° 2 (February 2020)
PermalinkConstraint based evaluation of generalized images generated by deep learning / Azelle Courtial (2020)
PermalinkCorrection of systematic radiometric inhomogeneity in scanned aerial campaigns using principal component analysis / Lâmân Lelégard in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)
PermalinkPermalinkPermalinkDeep learning for enrichment of vector spatial databases: Application to highway interchange / Guillaume Touya in ACM Transactions on spatial algorithms and systems, TOSAS, vol 6 n° 3 (May 2020)
![]()
Permalink