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From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 / Yousra Hamrouni in ISPRS Journal of photogrammetry and remote sensing, vol 171 (January 2021)
[article]
Titre : From local to global: A transfer learning-based approach for mapping poplar plantations at national scale using Sentinel-2 Type de document : Article/Communication Auteurs : Yousra Hamrouni, Auteur ; Eric Paillassa, Auteur ; Véronique Chéret, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 76 - 100 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] apprentissage automatique
[Termes IGN] base de données forestières
[Termes IGN] carte de la végétation
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] couvert forestier
[Termes IGN] échantillonnage
[Termes IGN] France (administrative)
[Termes IGN] image Sentinel-MSI
[Termes IGN] mise à jour de base de données
[Termes IGN] Populus (genre)
[Termes IGN] série temporelleRésumé : (auteur) Reliable estimates of poplar plantations area are not available at the French national scale due to the unsuitability and low update rate of existing forest databases for this short-rotation species. While supervised classification methods have been shown to be highly accurate in mapping forest cover from remotely sensed images, their performance depends to a great extent on the labelled samples used to build the models. In addition to their high acquisition cost, such samples are often scarce and not fully representative of the variability in class distributions. Consequently, when classification models are applied to large areas with high intra-class variance, they generally yield poor accuracies because of data shift issues. In this paper, we propose the use of active learning to efficiently adapt a classifier trained on a source image to spatially distinct target images with minimal labelling effort and without sacrificing the classification performance. The adaptation consists in actively adding to the initial local model new relevant training samples from other areas in a cascade that iteratively improves the generalisation capabilities of the classifier leading to a global model tailored to these different areas. This active selection relies on uncertainty sampling to directly focus on the most informative pixels for which the algorithm is the least certain of their class labels. Experiments conducted on Sentinel-2 time series revealed their high capacity to identify poplar plantations at a local scale with an average F-score ranging from 89.5% to 99.3%. For large area adaptation, the results showed that when the same number of training samples was used, active learning outperformed random sampling by up to 5% of the overall accuracy and up to 12% of the class F-score. Additionally, and depending on the class considered, the random sampling model required up to 50% more samples to achieve the same performance of an active learning-based model. Moreover, the results demonstrate the suitability of the derived global model to accurately map poplar plantations among other tree species with overall accuracy values up to 14% higher than those obtained with local models. The proposed approach paves the way for a national scale mapping in an operational context. Numéro de notice : A2021-013 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2020.10.018 Date de publication en ligne : 20/11/2020 En ligne : https://doi.org/10.1016/j.isprsjprs.2020.10.018 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96417
in ISPRS Journal of photogrammetry and remote sensing > vol 171 (January 2021) . - pp 76 - 100[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2021011 SL Revue Centre de documentation Revues en salle Disponible 081-2021013 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2021012 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Generative adversarial networks to generalise urban areas in topographic maps / Azelle Courtial (2021)
Titre : Generative adversarial networks to generalise urban areas in topographic maps Type de document : Article/Communication Auteurs : Azelle Courtial , Auteur ; Guillaume Touya , Auteur ; Xiang Zhang, Auteur Editeur : International Society for Photogrammetry and Remote Sensing ISPRS Année de publication : 2021 Collection : International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences, ISSN 1682-1750 num. 43-B4-2021 Projets : 1-Pas de projet / Conférence : ISPRS 2021, Commission 4, XXIV ISPRS Congress, Imaging today foreseeing tomorrow 05/07/2021 09/07/2021 Nice Virtuel France OA Archives Commission 4 Importance : pp 15 - 22 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] apprentissage profond
[Termes IGN] carte topographique
[Termes IGN] généralisation cartographique automatisée
[Termes IGN] réseau antagoniste génératif
[Termes IGN] zone urbaine
[Vedettes matières IGN] GénéralisationRésumé : (auteur) This article presents how a generative adversarial network (GAN) can be employed to produce a generalised map that combines several cartographic themes in the dense context of urban areas. We use as input detailed buildings, roads, and rivers from topographic datasets produced by the French national mapping agency (IGN), and we expect as output of the GAN a legible map of these elements at a target scale of 1:50,000. This level of detail requires to reduce the amount of information while preserving patterns; covering dense inner cities block by a unique polygon is also necessary because these blocks cannot be represented with enlarged individual buildings. The target map has a style similar to the topographic map produced by IGN. This experiment succeeded in producing image tiles that look like legible maps. It also highlights the impact of data and representation choices on the quality of predicted images, and the challenge of learning geographic relationships. Numéro de notice : C2021-016 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B4-2021-15-2021 Date de publication en ligne : 30/06/2021 En ligne : https://doi.org/10.5194/isprs-archives-XLIII-B4-2021-15-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98062
Titre : Land use planning for natural hazards Type de document : Monographie Auteurs : George D. Bathrellos, Éditeur scientifique ; Hariklia D. Skilodimou, Auteur Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 106 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03943-926-3 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] carte thématique
[Termes IGN] cartographie des risques
[Termes IGN] croissance urbaine
[Termes IGN] dégradation des sols
[Termes IGN] désertification
[Termes IGN] effondrement de terrain
[Termes IGN] érosion
[Termes IGN] géomorphologie
[Termes IGN] Grèce
[Termes IGN] inondation
[Termes IGN] montée du niveau de la mer
[Termes IGN] Népal
[Termes IGN] orage
[Termes IGN] planification
[Termes IGN] réseau de drainage
[Termes IGN] risque naturel
[Termes IGN] surveillance du littoral
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (éditeur) Natural hazard events are able to significantly affect the natural and artificial environment. In this context, changes in landforms due to natural disasters have the potential to affect and, in some cases, even restrict human interaction with the ecosystem. In order to minimize fatalities and reduce the economic impact that accompanies their occurrence, proper planning is crucial. Land use planning can play an important role in reducing current and future risks related to natural hazards. Land use changes can lead to natural hazards and vice versa: natural hazards affect land uses. Therefore, planners may take into account areas that are susceptible to natural hazards when selecting favorable locations for land use development. Appropriate land use planning can lead to the determination of safe and non-safe areas for urban activities. This Special Issue focuses on land use planning for natural hazards. In this context, various types of natural hazards, such as land degradation and desertification, coastal hazard, floods, and landslides, as well as their interactions with human activities, are presented. Note de contenu : 1- Combating land degradation and desertification: The land-use planning quandary
2- Coastal hazard vulnerability assessment based on geomorphic, oceanographic and demographic parameters: The case of the Peloponnese (Southern Greece)
3- Temporal and spatial analysis of flood occurrences in the drainage basin of Pinios River (Thessaly, Central Greece)
4- Flood hazard mapping of a rapidly urbanizing city in the foothills (Birendranagar, Surkhet) of Nepal
5- Physical and anthropogenic factors related to landslide activity in the Northern Peloponnese, GreeceNuméro de notice : 28441 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03943-926-3 En ligne : https://doi.org/10.3390/books978-3-03943-926-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98892
Titre : Lived and perceived space during lock-down in a sensitive map approach Type de document : Article/Communication Auteurs : Laurence Jolivet , Auteur ; Catherine Dominguès , Auteur ; Eric Mermet , Auteur ; Sevil Seten, Auteur Editeur : International Cartographic Association ICA - Association cartographique internationale ACI Année de publication : 2021 Collection : Proceedings of the ICA num. 4 Projets : 1-Pas de projet / Conférence : ICC 2021, 30th ICA international cartographic conference 14/12/2021 18/12/2021 Florence Italie OA Archives Commission 4 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] cartogramme
[Termes IGN] cartographie sensible
[Termes IGN] espace public
[Termes IGN] expérience scientifique
[Termes IGN] sentiment
[Termes IGN] utilisateur civil
[Vedettes matières IGN] CartologieRésumé : (auteur) The first lock-down in France due to the Covid-19 pandemic happened during spring 2020. It meant restrictions for everyone regarding reachable space and possible time length outside home. The seminar of sensitive mapping taking place in École des hautes études en sciences sociales (EHESS) went online and proposed an exercise to investigate the consequences of these statutory restrictions on individual lived and perceived space. The defined protocol of the exercise was based on the framework of the sensitive map approach. This approach adapts the principles of conventional cartography so that to favour personal information selection and design. Each participant of the seminar had the task to map their space. Displayed information should concern meaningful elements from their spatial environment. Other targeted information was sensitive information including emotions, feelings, and opinions as well as perceived elements from the five senses. The resulted map corpus offers diverse mapping creations. Each map contains several graphic items. Items are mainly cartographical displays enriched with non-cartographical drawings, pictures, photos, records, charts. Techniques were mixed: pen, fabrics, computer-based. The themes of displayed elements are about spatially-stable features like the dwelling, buildings remained open, green spaces, and about ephemeral and sensitive information like social interactions, people, perceived sounds, smells and feelings about the lock-down situation and the pandemic. Some maps have used or were inspired by topographic maps. Though in most maps, distances and topology are subjective. Sensitive mapping appeared as an interesting approach to collect individual testimonies and might be complementary to statistical studies. Numéro de notice : C2021-056 Affiliation des auteurs : UGE-LASTIG+Ext (2020- ) Thématique : GEOMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/ica-proc-4-50-2021 Date de publication en ligne : 03/12/2021 En ligne : https://doi.org/10.5194/ica-proc-4-50-2021 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99435
Titre : Mapping and Monitoring Forest Cover Type de document : Monographie Auteurs : Russell G. Congalton, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2021 Importance : 144 p. ISBN/ISSN/EAN : 978-3-0365-2043-8 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] carte forestière
[Termes IGN] couvert forestier
[Termes IGN] forêt
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] inventaire forestier local
[Termes IGN] mangroveNote de contenu : - Mapping and Monitoring Forest Cover
- Spatial and Temporal Changes in Vegetation in the Ruoergai Region, China
- Monitoring Mangrove Forest Degradation and Regeneration: Landsat Time Series Analysis of Moisture and Vegetation Indices at Rabigh Lagoon, Red Sea
- Monitoring Carbon Stock and Land-Use Change in 5000-Year-Old Juniper Forest Stand of Ziarat, Balochistan, through a Synergistic Approach
- Forest Cover Mapping Based on a Combination of Aerial Images and Sentinel-2 Satellite Data Compared to National Forest Inventory Data
- Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory
- A Comparison of Forest Tree Crown Delineation from Unmanned Aerial Imagery Using Canopy Height Models vs. Spectral LightnessNuméro de notice : 17141 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-0365-2044-5 En ligne : https://doi.org/10.3390/books978-3-0365-2044-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98631 PermalinkPermalinkA method of hydrographic survey technology selection based on the decision tree supervised learning / Ivana Golub Medvešek (2021)PermalinkMise en place d’une infrastructure de données spatiales sur le risque de piqures de tiques / Lilian Calas (2021)PermalinkModelling landslide hazards under global changes: the case of a Pyrenean valley / Séverine Bernardie in Natural Hazards and Earth System Sciences, vol 21 n° 1 (January 2021)PermalinkMulti-modal temporal attention models for crop mapping from satellite time series / Vivien Sainte Fare Garnot (2021)PermalinkParticiper à la construction de la base de données des toponymes maritimes du SHOM / Solenn Tual (2021)PermalinkProposition d’un référentiel de description et de détection de la végétation dans une agglomération / Mathilde Segaud (2021)PermalinkPermalinkRemotely-sensed rip current dynamics and morphological control in high-energy beach environments / Isaac Rodriguez Padilla (2021)PermalinkSemantic segmentation of sea ice type on Sentinel-1 SAR data using convolutional neural networks / Alissa Kouraeva (2021)PermalinkSherloc: a knowledge-driven algorithm for geolocating microblog messages at sub-city level / Laura Di Rocco in International journal of geographical information science IJGIS, vol 35 n° 1 (January 2021)PermalinkSpatial characterization and distribution modelling of Ensete ventricosum (wild and cultivated) in Ethiopia / Meron Awoke Eshetae in Geocarto international, vol 36 n° 1 ([01/01/2021])PermalinkSuivi de la rotation des cultures à partir de séries temporelles d’images satellite / Félix Quinton (2021)PermalinkSuivi des vignes par télédétection de proximité : le deep learning au service de l’agriculture de précision / Sami Beniaouf (2021)PermalinkPermalinkPermalinkPermalinkTélédétection et intégration de connaissances via la modélisation spatiale pour une cartographie plus cohérente des systèmes agricoles complexes / Arthur Crespin-Boucaud (2021)PermalinkPermalink