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Hyperspectral imagery and urban areas: results of the HYEP project / Christiane Weber in Revue Française de Photogrammétrie et de Télédétection, n° 224 (2022)  

Public [article]  inRevue Française de Photogrammétrie et de Télédétection > n° 224 (2022) . - pp 75 - 92 Titre : Hyperspectral imagery and urban areas: results of the HYEP project Type de document : Article/Communication Auteurs : Christiane Weber, Auteur ; Xavier Briottet , Auteur ; Thomas Houet, Auteur ; Sébastien Gadal, Auteur ; Rahim Aguejdad, Auteur ; Yannick Deville, Auteur ; Mauro Dalla Mura, Auteur ; Clément Mallet , Auteur ; Arnaud Le Bris , Auteur ; et al., Auteur Année de publication : 2022 Projets : HYEP / Weber, Christiane Article en page(s) : pp 75 - 92 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] analyse comparative [Termes IGN] détection d'objet [Termes IGN] fusion d'images [Termes IGN] image hyperspectrale [Termes IGN] Lituanie [Termes IGN] milieu urbain [Termes IGN] panneau photovoltaïque [Termes IGN] surface imperméable [Termes IGN] Toulouse Résumé : (Auteur) The HYEP project (ANR HYEP 14-CE22-0016-01 Hyperspectral imagery for Environmental urban Planning - Mobility and Urban Systems Programme - 2014) confirmed the interest of a global approach to the urban environment by remote sensing and in particular by using hyperspectral imaging (HI). The interest of hyperspectral images lies in the range of information provided over wavelengths from 0.4 to 4 μm; they thus provide access to spectral quantities of interest and to chemical or biophysical parameters of the surface. HYEP's objective was to specify this and to propose a panel of methods and treatments taking into account the characteristics of other existing sensors in order to compare their performance. The developments carried out were applied and evaluated on hyperspectral airborne images acquired in Toulouse and Kaunas (Lithuania), also used to synthesize space systems: Sentinel-2, Hypxim/Biodiversity and Pleiades. Among the locks identified were those related to improving the spatial capabilities of the sensors and spatial scale changes, which were partially overcome by fusion and sharpening approaches, which proved to be successful. After a description of our hyperspectral data set acquired over Toulouse, an analysis is conducted on several existing and accessible spectral databases. Then, the chosen methods are presented. They include extraction, fusion and classification methods, which are then applied on our dataset synthetized at different spatial resolution to evaluate the benefits and the complementarity of hyperspectral imagery in comparison with other traditional sensors. Some specific applications are investigated of interest for urban planners: impervious soil map, vegetation species cartography and detection of solar panels. Finally, discussion and perspectives are presented. Numéro de notice : A2022-941 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Autre URL associée : Hal Thématique : IMAGERIE/URBANISME Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : 10.52638/rfpt.2022.589 Date de publication en ligne : 22/12/2022 En ligne : https://dx.doi.org/10.52638/rfpt.2022.589 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102831 [article]

Integration of radar and optical Sentinel images for land use mapping in a complex landscape (case study: Arasbaran Protected Area) / Vahid Nasiri in Arabian Journal of Geosciences, vol 15 n° 24 (December 2022)  

Public [article]  inArabian Journal of Geosciences > vol 15 n° 24 (December 2022) . - n° 1759 Titre : Integration of radar and optical Sentinel images for land use mapping in a complex landscape (case study: Arasbaran Protected Area) Type de document : Article/Communication Auteurs : Vahid Nasiri, Auteur ; Arnaud Le Bris , Auteur ; Ali Asghar Darvishsefat, Auteur ; Fardin Moradi, Auteur Année de publication : 2022 Projets : 1-Pas de projet / Weber, Christiane Article en page(s) : n° 1759 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] aire protégée [Termes IGN] carte d'occupation du sol [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] classification par maximum de vraisemblance [Termes IGN] classification par séparateurs à vaste marge [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR Résumé : (auteur) Considering the importance of accurate and up-to-date land use/cover (LULC) maps and in a situation of fast LULC changes, an accurate mapping of complex landscapes requires real-time high-resolution remote sensed data and powerful classification algorithms. The new ESA Copernicus satellites Sentinel-1 (S-1) and Sentinel-2 (S-2) have contributed to the effective monitoring of the Earth’s surface. This paper aims at assessing the potential of mono-temporal S-1 and S-2 satellite images and three common classification algorithms including maximum likelihood (ML), support vector machine (SVM), and random forest (RF) for LULC classification. The research methodology consists of a sequence of tasks including data collection and preprocessing, the extraction of texture and spectral features, the definition of several feature set configurations, classification, and accuracy assessment. Based on the results, using S-1 data alone leads to quite poor results, even though dual polarimetric C-band and texture features increased the classification accuracy. The S-2 data outperformed the S-1 data in terms of overall and class level accuracies. A combined use of S-1 and S-2 satellite images involving extracted features from both sources led to the best result for identifying all classes. This emphasizes the critical importance of using multi-modal datasets and different features in the LULC classification. Among classification algorithms, the SVM led to the highest accuracies irrespective of the dataset. To sum it up, according to the applied methodology and results, S-1 and S-2 data can provide optimal and up-to-date information for LULC mapping using non-parametric classifiers as SVM or RF. Numéro de notice : A2022-699 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s12517-022-11035-z Date de publication en ligne : 07/12/2022 En ligne : https://doi.org/10.1007/s12517-022-11035-z Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102253 [article]

Classification of vegetation classes by using time series of Sentinel-2 images for large scale mapping in Cameroon / Hermann Tagne in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-3-2022 (2022 edition)  

Public [article]  inISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > vol V-3-2022 (2022 edition) . - pp 673 - 680 Titre : Classification of vegetation classes by using 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 Année de publication : 2022 Projets : TOSCA Parcelle / Le Bris, Arnaud Article en page(s) : pp 673 - 680 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection [Termes IGN] Cameroun [Termes IGN] carte de la végétation [Termes IGN] classification par forêts d'arbres décisionnels [Termes IGN] fusion d'images [Termes IGN] image Sentinel-MSI [Termes IGN] occupation du sol [Termes IGN] série temporelle Résumé : (auteur) Sentinel-2 satellites provide dense image time series exhibiting high spectral, spatial and temporal resolutions. These images are in particular of utter interest for Land-Cover (LC) mapping at large scales. 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 Very High Resolution national topographic geodatabase. The ι2 framework is adopted and tested for the specificity of the country. Here, experiments focus on generic vegetation 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 (>94% in Overall Accuracy), allowing to provide a first step towards finer-grained map retrieval. Numéro de notice : A2022-426 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.5194/isprs-annals-V-3-2022-673-2022 Date de publication en ligne : 18/05/2022 En ligne : https://doi.org/10.5194/isprs-annals-V-3-2022-673-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100731 [article]

Automatic algorithm for georeferencing historical-to-nowadays aerial images acquired in natural environments / Daniela Craciun (2022)  

Public Titre : Automatic algorithm for georeferencing historical-to-nowadays aerial images acquired in natural environments Type de document : Article/Communication Auteurs : Daniela Craciun , Auteur ; Arnaud Le Bris , Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2022 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B2 Projets : HIATUS / Giordano, Sébastien Conférence : ISPRS 2022, Commission 2, 24th ISPRS international congress, Imaging today, foreseeing tomorrow 06/06/2022 11/06/2022 Nice France OA ISPRS Archives Importance : pp 21 - 28 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Photogrammétrie numérique [Termes IGN] appariement d'images [Termes IGN] estimation de pose [Termes IGN] géoréférencement [Termes IGN] gradient [Termes IGN] histogramme [Termes IGN] image ancienne [Termes IGN] milieu naturel [Termes IGN] modèle numérique de surface Résumé : (auteur) Automatic georeferencing for historical-to-nowadays aerial images represents the main ingredient for supplying territory evolution analysis and environmental monitoring. Existing georeferencing methods based on feature extraction and matching reported successful results for multi-epoch aerial images acquired in structured and man-made environments. While improving the state-of-the-art of the multi-epoch georeferencing problem, such frameworks present several limitations when applied to unstructured scenes, such as natural feature-less environments, characterized by homogenous or texture-less areas. This is mainly due to the lack of structured areas which often results in sparse and ambiguous feature matches, introducing inconsistencies during the pose estimation process. This paper addresses the automatic georeferencing problem for historical aerial images acquired in unstructured natural environments. The research work presented in this paper introduces a feature-less algorithm designed to perform historical-to-nowadays image matching for pose estimation in a fully automatic fashion. The proposed algorithm operates within two stages: (i) 2D patch extraction and matching and (ii) 3D patch-based local alignment. The final output is a set of 3D patch matches and the 3D rigid transformation relating each homologous patches. The obtained 3D point matches are designed to be injected into traditional multi-views pose optimisation engines. Experimental results on real datasets acquired over Fabas area situated in France demonstrate the effectiveness of the proposed method. Our findings illustrate that the proposed georeferencing technique provides accurate results in presence of large periods of time separating historical from nowadays aerial images (up to 48 years time span). Numéro de notice : C2022-020 Affiliation des auteurs : UGE-LASTIG (2020- ) Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B2-2022-21-2022 Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.5194/isprs-archives-XLIII-B2-2022-21-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100846

Implementation of the log-transformed band ratio algorithm on images of WorldView-3 and Sentinel-2 for bathymetry mapping of a pocket beach of Malta / Antoine Cornu (2022)  

Public Titre : Implementation of the log-transformed band ratio algorithm on images of WorldView-3 and Sentinel-2 for bathymetry mapping of a pocket beach of Malta Type de document : Article/Communication Auteurs : Antoine Cornu, Auteur ; Luciano Galone, Auteur ; Arnaud Le Bris , Auteur ; Sebastiano d' Amico, Auteur ; Adam Gauci, Auteur ; Manchun Lei , Auteur ; Emanuele Colica, Auteur Editeur : New-York : IEEE Computer society Année de publication : 2022 Conférence : MetroSea 2022, IEEE International Workshop on Metrology for the Sea; Learning to Measure Sea Health Parameters 03/10/2022 05/10/2022 Milazzo Italie OA ISPRS Archives Importance : pp 493 - 496 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique [Termes IGN] bathymétrie [Termes IGN] image Sentinel-MSI [Termes IGN] image Worldview [Termes IGN] littoral [Termes IGN] profondeur Mots-clés libres : log-transformed band ratio  depth retrieval Résumé : (auteur) Several methods are in place to calculate shallow water bathymetry from satellite images, such as Worldview 3 or Sentinel-2, which have differences in their resolution and their accessibility. The method used in this research is the log- transformed band ratio between the blue channel and the green channel. This document compares the results of this method with the Worldview 3 and Sentinel-2 images. Numéro de notice : C2022-045 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/MetroSea55331.2022.9950982 En ligne : https://doi.org/10.1109/MetroSea55331.2022.9950982 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102290

Improving local adaptive filtering method employed in radiometric correction of analogue airborne campaigns / Lâmân Lelégard (2022)  

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Products and services of the Urban THEIA Scientific Expertise Centre / Anne Puissant (2022)    

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Unmanned aerial vehicles (UAV)-based canopy height modeling under leaf-on and leaf-off conditions for determining tree height and crown diameter (Case study: Hyrcanian mixed forest) / Vahid Nasiri in Canadian Journal of Forest Research, Vol 51 n° 7 (July 2021)  

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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)  

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AI4GEO: a data intelligence platform for 3D geospatial mapping / Pierre-Marie Brunet (2021)  

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An efficient representation of 3D buildings: application to the evaluation of city models / Oussama Ennafii (2021)  

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Can SPOT-6/7 CNN semantic segmentation improve Sentinel-2 based land cover products? sensor assessment and fusion / Olivier Stocker in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol V-2-2020 (August 2020)  

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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)  

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Correction 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)  

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Use of automated change detection and VGI sources for identifying and validating urban land use change / Ana-Maria Olteanu-Raimond in Remote sensing, vol 12 n° 7 (April 2020)  

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