Descripteur
Documents disponibles dans cette catégorie (1260)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
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 Comparison of multi-seasonal Landsat 8, Sentinel-2 and hyperspectral images for mapping forest alliances in Northern California / Matthew L. Clark in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
[article]
Titre : Comparison of multi-seasonal Landsat 8, Sentinel-2 and hyperspectral images for mapping forest alliances in Northern California Type de document : Article/Communication Auteurs : Matthew L. Clark, Auteur Année de publication : 2020 Article en page(s) : pp 26 - 40 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] analyse comparative
[Termes IGN] apprentissage automatique
[Termes IGN] Californie (Etats-Unis)
[Termes IGN] carte forestière
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] couvert végétal
[Termes IGN] image AVIRIS
[Termes IGN] image hyperspectrale
[Termes IGN] image Landsat-8
[Termes IGN] image Sentinel-MSI
[Termes IGN] occupation du sol
[Termes IGN] Short Waves InfraRedRésumé : (Auteur) The current era of earth observation now provides constellations of open-access, multispectral satellite imagery with medium spatial resolution, greatly increasing the frequency of cloud-free data for analysis. The Landsat satellites have a long historical record, while the newer Sentinel-2 (S2) satellites offer higher temporal, spatial and spectral resolution. The goal of this study was to evaluate the relative benefits of single- and multi-seasonal multispectral satellite data for discriminating detailed forest alliances, as defined by the U.S. National Vegetation Classification system, in a Mediterranean-climate landscape (Sonoma County, California). Results were compared to a companion analysis of simulated hyperspectral satellite data (HyspIRI) for the same study site and reference data (Clark et al., 2018). Experiments used real and simulated S2 and Landsat 8 (L8) data. Simulated S2 and L8 were from HyspIRI images, thereby focusing results on differences in spectral resolution rather than other confounding factors. The Support Vector Machine (SVM) classifier was used in a hierarchical classification of land-cover (Level 1), followed by alliances (Level 2) in forest pixels, and included summer-only and multi-seasonal sets of predictor variables (bands, indices and bands plus indices). Both real and simulated multi-seasonal multispectral variables significantly improved overall accuracy (OA) by 0.2–1.6% for Level 1 tree/no tree classifications and 3.6–25.8% for Level 2 forest alliances. Classifiers with S2 variables tended to be more accurate than L8 variables, particularly for S2, which had 0.4–2.1% and 5.1–11.8% significantly higher OA than L8 for Level 1 tree/no tree and Level 2 forest alliances, respectively. Combining multispectral bands and indices or using just bands was generally more accurate than relying on just indices for classification. Simulated HyspIRI variables from past research had significantly greater accuracy than real L8 and S2 variables, with an average OA increase of 8.2–12.6%. A final alliance-level map used for a deeper analysis used simulated multi-seasonal S2 bands and indices, which had an overall accuracy of 74.3% (Kappa = 0.70). The accuracy of this classification was only 1.6% significantly lower than the best HyspIRI-based classification, which used multi-seasonal metrics (Clark et al., 2018), and there were alliances where the S2-based classifier was more accurate. Within the context of these analyses and study area, S2 spectral-temporal data demonstrated a strong capability for mapping global forest alliances, or similar detailed floristic associations, at medium spatial resolutions (10–30 m). Numéro de notice : A2020-011 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2019.11.007 Date de publication en ligne : 14/11/2019 En ligne : https://doi.org/10.1016/j.isprsjprs.2019.11.007 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94399
in ISPRS Journal of photogrammetry and remote sensing > vol 159 (January 2020) . - pp 26 - 40[article]Réservation
Réserver ce documentExemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2020011 RAB Revue Centre de documentation En réserve L003 Disponible 081-2020013 DEP-RECP Revue LASTIG Dépôt en unité Exclu du prêt 081-2020012 DEP-RECF Revue Nancy Dépôt en unité Exclu du prêt Détermination conjointe des inondations et du type d’eau au moyen de l’imagerie multi-spectrale / Sabrine Amzil (2020)
Titre : Détermination conjointe des inondations et du type d’eau au moyen de l’imagerie multi-spectrale Type de document : Mémoire Auteurs : Sabrine Amzil, Auteur Editeur : Strasbourg : Institut National des Sciences Appliquées INSA Strasbourg Année de publication : 2020 Importance : 92 p. Format : 21 x 30 cm Note générale : bibliographie
Mémoire de soutenance de diplôme d'ingénieur INSA spécialité TopographieLangues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] Amazone (fleuve)
[Termes IGN] Amazonie
[Termes IGN] image Aqua-MODIS
[Termes IGN] image en couleur
[Termes IGN] image multibande
[Termes IGN] image optique
[Termes IGN] image Sentinel-SAR
[Termes IGN] image Terra-MODIS
[Termes IGN] indice d'humidité
[Termes IGN] inondation
[Termes IGN] Normalized Difference Vegetation Index
[Termes IGN] série temporelleIndex. décimale : INSAS Mémoires d'ingénieur de l'INSA Strasbourg - Topographie, ex ENSAIS Résumé : (auteur) L’Amazonie, en Amérique du Sud, est connue pour ses plaines d’inondations et ses régimes saisonniers de précipitations très irréguliers à cause de plusieurs facteurs naturels et anthropiques. Les eaux amazoniennes se caractérisent non seulement par leurs grandes étendues mais également par la diversité des couleurs de ses fleuves et affluents. Ce projet de fin d’études vise à déterminer conjointement l’extension des inondations et les types d’eaux du bassin amazonien (eaux claires, laiteuses, noires, ...) par analyse de séries temporelles d’images multispectrales acquises par le capteur MODIS des satellites Aqua et Terra au cours de l’année 2017. La détection des inondations a été réalisée en se basant sur une combinaison d’indices spectraux NDVI, SWIb et AWEI après la recherche des valeurs seuils de chacun de ces indices. Tandis que la classification des types d’eaux s’effectue en fonction de la réponse de la valeur moyenne mensuelle du SWIb. Cette étude nous permet donc de mieux comprendre le bilan hydrologique et sédimentaire des zones d’inondation et fleuves amazoniens en se basant uniquement sur les apports de la télédétection optique. Note de contenu : Introduction
1- Etat de l'art
2- Création des méthodes de détection et classification des eaux
3- Evaluation et validation de la méthode
Conclusion et perspectivesNuméro de notice : 28577 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Mémoire ingénieur INSAS Organisme de stage : LEGOS (Toulouse) DOI : sans En ligne : http://eprints2.insa-strasbourg.fr/4187/1/M%C3%A9moire_PFE_AMZIL.pdf Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97884 Fusion of 3D point clouds and hyperspectral data for the extraction of geometric and radiometric features of trees / Eduardo Alejandro Tusa Jumbo (2020)
Titre : Fusion of 3D point clouds and hyperspectral data for the extraction of geometric and radiometric features of trees Type de document : Thèse/HDR Auteurs : Eduardo Alejandro Tusa Jumbo, Auteur ; Jocelyn Chanussot, Directeur de thèse ; Jean-Matthieu Monnet, Encadrant ; Mauro Dalla Mura, Encadrant ; Jean-Baptiste Barré, Encadrant Editeur : Grenoble : Université de Grenoble Année de publication : 2020 Importance : 153 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse pour obtenir le grade de docteur de l'Université Grenoble Alpes, Signal image parole TelecomsLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] Alpes (France)
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] espèce végétale
[Termes IGN] extraction de la végétation
[Termes IGN] forêt alpestre
[Termes IGN] fusion de données multisource
[Termes IGN] image hyperspectrale
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier local
[Termes IGN] semis de points
[Termes IGN] télédétection par lidar
[Termes IGN] télédétection spatialeIndex. décimale : THESE Thèses et HDR Résumé : (Auteur) Mountain forests provide environmental ecosystem services (EES) to communities: supplying of recreational landscapes, protection against natural hazards, supporting biodiversity conservation, among others. The preservation of these EES through space and time requires a good characterization of the resources. Especially in mountains, stands are very heterogeneous and timber harvesting is economically possible thanks to trees of higher value. This is why we want to be able to map each tree and estimate its characteristics, including quality, which is related to its shape and growth conditions. Field inventories are not able to provide a wall to wall cover of detailed tree-level information on a large scale. On the other hand, remote sensing tools seem to be a promising technology because of the time efficient and the affordable costs for studying forest areas. LiDAR data provide detailed information from the vertical distribution and location of the trees, but it is limited for mapping species. Hyperspectral data are associated to absorption features in the canopy reflectance spectrum, but is not effective for characterizing tree geometry. Hyperspectral and LiDAR systems provide independent and complementary data that are relevant for the assessment of biophysical and biochemical attributes of forest areas. This PhD thesis deals with the fusion of LiDAR and hyperspectral data to characterize individual forest trees. The leading idea is to improve methods to derive forest information at tree-level by extracting geometric and radiometric features. The contributions of this research work relies on: i) an updated review of data fusion methods of LiDAR and hyperspectral data for forest monitoring, ii) an improved 3D segmentation algorithm for delineating individual tree crowns based on Adaptive Mean Shift (AMS3D) and an ellipsoid crown shape model, iii) a criterion for feature selection based on random forests score, 5-fold cross validation and a cumulative error function for forest tree species classification. The two main methods used to derive forest information at tree level are tested with remote sensing data acquired in the French Alps. Note de contenu : 1 Introduction
1.1 Forest
1.2 Principles of remote sensing
1.3 Motivation
1.4 Objectives
1.5 Thesis structure
2. Data Fusion 15
2.1 Principles of fusion
2.2 Low-level
2.3 Medium-level
2.4 High-level
2.5 Applications
3. Material 32
3.1 Field data
3.2 Study areas
3.3 ALS and hyperspectral data
4 ITC Delineation
4.1 Introduction
4.2 MS segmentation
4.3 AMS3D based on crown shape model
4.4 Experimental analysis
4.5 Conclusion
5. Tree Species Classification
5.1 Introduction
5.2 Study area
5.3 Methodology
5.4 Results and discussion
5.5 Conclusions
6. Conclusion and work perspectives
6.1 How data processing methods are applied in each level of data fusion for forest monitoring?
6.2 How a crown shape model can improve the segmentation of individual tree crowns?
6.3 Which feature combination contribute to characterize the forest tree species composition?Numéro de notice : 26582 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Signal image parole Telecoms : Grenoble : 2020 Organisme de stage : Grenoble Images Parole Signal Automatique GIPSA-lab nature-HAL : Thèse DOI : sans Date de publication en ligne : 30/07/2021 En ligne : https://tel.archives-ouvertes.fr/tel-03212453/document Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98403
Titre : Geo-spatial analysis in hydrology Type de document : Monographie Auteurs : Qiming Zhou, Éditeur scientifique ; Jianfeng Li, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2020 Importance : 124 p. Format : 21 x 30 cm ISBN/ISSN/EAN : 978-3-03936-981-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] barrage
[Termes IGN] bassin hydrographique
[Termes IGN] évapotranspiration
[Termes IGN] hydrographie
[Termes IGN] image optique
[Termes IGN] image Sentinel-MSI
[Termes IGN] inondation
[Termes IGN] modèle hydrographique
[Termes IGN] modèle numérique de surface
[Termes IGN] occupation du sol
[Termes IGN] ruissellement
[Termes IGN] système d'information géographique
[Termes IGN] utilisation du solRésumé : (auteur) Geo-spatial analysis has become an essential component of hydrological studies to process and examine geo-spatial data such as hydrological variables (e.g., precipitation and discharge) and basin characteristics (e.g., DEM and land use land cover). The advancement of the data acquisition technique helps accumulate geo-spatial data with more extensive spatial coverage than traditional in-situ observations. The development of geo-spatial analytic methods is beneficial for the processing and analysis of multi-source data in a more efficient and reliable way for a variety of research and practical issues in hydrology. This book is a collection of the articles of a published Special Issue Geo-Spatial Analysis in Hydrology in the journal ISPRS International Journal of Geo-Information. The topics of the articles range from the improvement of geo-spatial analytic methods to the applications of geo-spatial analysis in emerging hydrological issues. The results of these articles show that traditional hydrological/hydraulic models coupled with geo-spatial techniques are a way to make streamflow simulations more efficient and reliable for flood-related decision making. Geo-spatial analysis based on more advanced methods and data is a reliable resolution to obtain high-resolution information for hydrological studies at fine spatial scale. Note de contenu : 1- Dynamic 3D simulation of flood risk based on the integration of spatio-temporal GIS and hydrodynamic models
2- Integrated hazard modeling for simulating torrential stream response to flash flood events
3- Consideration of level of confidence within multi-approach satellite-derived bathymetry
4- A method of watershed delineation for flat terrain using Sentinel-2A imagery and DEM: A case study of the Taihu basin
5- Monitoring the water quality of small water bodies using high-resolution remote sensing data
6- Estimation of crop water deficit in lower Bari doab, Pakistan using reflection-based crop coefficientNuméro de notice : 28625 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.3390/books978-3-03936-981-2 En ligne : https://doi.org/10.3390/books978-3-03936-981-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99556 PermalinkIndividual tree detection and classification for mapping pine wilt disease using multispectral and visible color imagery acquired from unmanned aerial vehicle / Takeshi Hoshikawa in Journal of The Remote Sensing Society of Japan, vol 40 n° 1 (2020)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalink