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Titre : Télédétection et modélisation spatiale : Applications à la surveillance et au contrôle des maladies liées aux moustiques Type de document : Monographie Auteurs : Annelise Tran, Éditeur scientifique ; Eric Daudé, Éditeur scientifique ; Thibault Catry, Éditeur scientifique Editeur : Versailles : Quae Année de publication : 2022 Importance : 148 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-2-7592-3629-9 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] analyse multicritère
[Termes IGN] cartographie des risques
[Termes IGN] distribution spatiale
[Termes IGN] image Landsat-8
[Termes IGN] image Landsat-ETM+
[Termes IGN] image multibande
[Termes IGN] image Terra-MODIS
[Termes IGN] maladie parasitaire
[Termes IGN] maladie tropicale
[Termes IGN] modélisation spatiale
[Termes IGN] Normalized Difference Water Index
[Termes IGN] surveillance sanitaire
[Termes IGN] température de l'air
[Termes IGN] TRMMRésumé : (éditeur) Mosquitoes are vectors of many disease-causing agents, such as malaria, dengue, chikungunya and yellow fever. According to the World Health Organisation, they cause several hundred thousand deaths each year. They are also the cause of zoonoses, such as Rift Valley fever and West Nile fever. In this context, there is a great need for operational tools to guide surveillance and control actions, both in the South - tropical and subtropical areas are the most affected by mosquito-borne diseases - and in the North, where the establishment of new species such as the tiger mosquito increases the risk of disease emergence. Earth observation imagery is of great interest to meet these needs: the spatial distribution and temporal dynamics of mosquitoes are influenced by climatic (temperature, precipitation, humidity) and environmental (availability of water areas, vegetation) variables, indicators of which can be derived from satellite imagery. Many recent studies have developed innovative methods combining remote sensing and spatial modelling to predict the spatial and temporal dynamics of mosquito vectors and associated diseases. Beyond the feasibility study, some of these methods have led to tools and processing chains that are now operational and used by public health actors and vector control operators. This book, intended for students and researchers as well as public health actors, presents a summary of this research work and these tools. Note de contenu : Introduction générale
Partie I- Informations spatiales pour la surveillance des moustiques vecteurs et des maladies associées
1- Liens entre moustiques vecteurs et environnement : apport des méthodes de télédétection satellite
2- Indices spectraux et classifications d’images multispectrales pour la cartographie du risque vectoriel
3- Estimation des températures de l’air à partir d’images satellite et de stations météorologiques
4- Du recensement au bâtiment : génération de populations synthétiques
5- Texture des images satellite et caractérisation des milieux urbains favorables aux moustiques vecteurs
Partie II- Analyser et prédire l’effet de variables environnementales sur la distribution et la dynamique des moustiques vecteurs
6- Modèles basés sur les données : cartographier la distribution spatiale des vecteurs
7- Modèles fondés sur les connaissances : exemple d’un outil d’évaluation multicritère pour la santé publique
8- Arbocarto : un modèle mécaniste fondé sur le cycle de vie des moustiques Aedes
9- Simulation spatiale du risque de propagation de la dengue à partir de modèles comportementaux vecteurs et hôtes
Conclusion générale et perspectivesNuméro de notice : 24096 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.35690/978-2-7592-3629-9 En ligne : https://doi.org/10.35690/978-2-7592-3629-9 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102570
Titre : the EUROSDR time benchmark for historical aerial images Type de document : Article/Communication Auteurs : E.M. Farella, Auteur ; L. Morelli, Auteur ; Fabio Remondino, Auteur ; Jon P. Mills, Auteur ; Norbert Haala, Auteur ; Joep Crompvoets, 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 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 1175 - 1182 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image
[Termes IGN] aérotriangulation
[Termes IGN] image aérienne
[Termes IGN] image ancienne
[Termes IGN] image multitemporelle
[Termes IGN] modèle numérique de surface
[Termes IGN] modèle numérique de terrain
[Termes IGN] orthophotographieMots-clés libres : benchmark Résumé : (auteur) Automatic photogrammetric processing of historical (or archival) aerial photos is still a challenging task, particularly in cases of missing ancillary information, low radiometric and image quality, limited stereo coverage or large temporal span. However, with recent advances in photogrammetry and Artificial Intelligence (AI) algorithms for image processing and interpretation, an increasing number of applications are now feasible. The article presents the TIME (hisTorical aerIal iMagEs) benchmark (https://time.fbk.eu/), promoted by EuroSDR to explore the potential of historical aerial images. Realized in collaboration with various European NMCAs, the benchmark has garnered aerial image blocks and time series imagery captured since the 1950s. To support the photogrammetric processing of the digitized photos, ancillary data are supplied with available information about flight missions, taking cameras, and ground control points (GCPs). Several diverse investigations have been undertaken with the benchmark datasets, all captured over historical urban areas or landscapes. The paper describes the benchmark datasets and some potential research topics, presenting several tests and analyses realized with the collated and shared data. Numéro de notice : C2022-021 Affiliation des auteurs : non IGN Thématique : IMAGERIE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.5194/isprs-archives-XLIII-B2-2022-1175-2022 Date de publication en ligne : 30/05/2022 En ligne : http://dx.doi.org/10.5194/isprs-archives-XLIII-B2-2022-1175-2022 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=100847
Titre : Traitement possibiliste d'images, application au recalage d'images Type de document : Thèse/HDR Auteurs : Wissal Ben Markouza, Auteur ; Basel Solaiman, Directeur de thèse ; Khaled Bsaïes, Directeur de thèse Editeur : Institut Mines-Télécom Atlantique IMT Atlantique Année de publication : 2022 Importance : 151 p. Format : 21 x 30 cm Note générale : Bibliographie
Thèse de Doctorat de l'Ecole Nationale Supérieure Mines-Télécom Atlantique, Spécialité Signal, image, visionLangues : Français (fre) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] appariement d'images
[Termes IGN] classification dirigée
[Termes IGN] extraction de traits caractéristiques
[Termes IGN] information sémantique
[Termes IGN] niveau de gris (image)
[Termes IGN] optimisation (mathématiques)
[Termes IGN] recalage d'image
[Termes IGN] sous ensemble flou
[Termes IGN] théorie des possibilitésIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Dans ce travail, nous proposons un système de recalage géométrique possibiliste qui fusionne les connaissances sémantiques et les connaissances au niveau du gris des images à recaler. Les méthodes de recalage géométrique existantes se reposent sur une analyse des connaissances au niveau des capteurs lors de la détection des primitives ainsi que lors de la mise en correspondance. L'évaluation des résultats de ces méthodes de recalage géométrique présente des limites au niveau de la perfection de la précision causées par le nombre important de faux amers. L’idée principale de notre approche proposée est de transformer les deux images à recaler en un ensemble de projections issues des images originales (source et cible). Cet ensemble est composé des images nommées « cartes de possibilité », dont chaque carte comporte un seul contenu et présente une distribution possibiliste d’une classe sémantique des deux images originales. Le système de recalage géométrique basé sur la théorie de possibilités proposé présente deux contextes : un contexte supervisé et un contexte non supervisé. Pour le premier cas de figure nous proposons une méthode de classification supervisée basée sur la théorie des possibilités utilisant les modèles d'apprentissage. Pour le contexte non supervisé, nous proposons une méthode de clustering possibiliste utilisant la méthode FCM-multicentroide. Les deux méthodes proposées fournissent en résultat les ensembles de classes sémantiques des deux images à recaler. Nous créons par la suite, les bases de connaissances pour le système de recalage possibiliste proposé. Nous avons amélioré la qualité du recalage géométrique existant en termes de perfection de précision, de diminution du nombre de faux amers et d'optimisation de la complexité temporelle. Note de contenu : Introduction générale
1- Etat de l'art
2- Recalage d'images : approche géométrique
3- estimation des distributions des possibilités pour le recalage géométrique
4- Systeme de recalage possibiliste
5- Expérimentation et évaluation du système de recalage possibiliste
Conclusions et perspectivesNuméro de notice : 24088 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Signal, image, vision : Mines-Télécom Atlantique : 2022 Organisme de stage : Laboratoire de Traitement de l'Information Medicale DOI : sans En ligne : https://theses.hal.science/tel-03917545 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102480
Titre : UAVs for the environmental sciences : Methods and applications Type de document : Monographie Auteurs : Annette Eltner, Éditeur scientifique ; Dirk Hoffmeister, Éditeur scientifique ; Andreas Kaiser, Éditeur scientifique ; et al., Auteur Editeur : Darmstadt : Wissenschaftliche Buchgesellschaft Année de publication : 2022 Importance : 492 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-534-40590-9 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] analyse comparative
[Termes IGN] droit
[Termes IGN] droit européen
[Termes IGN] étalonnage de capteur (imagerie)
[Termes IGN] géoréférencement
[Termes IGN] image captée par drone
[Termes IGN] matériel
[Termes IGN] navigation inertielle
[Termes IGN] photogrammétrie aérienne
[Termes IGN] plan de vol
[Termes IGN] récepteur GNSS
[Termes IGN] semis de pointsRésumé : (éditeur) This book gives an overview of the usage of UAVs in environmental sciences covering technical basics, data acquisition with different sensors, data processing schemes and illustrating various examples of application. Note de contenu : 1- Basics
2- Data acquisition
3- Data analysis
4- ApplicationsNuméro de notice : 24097 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Recueil / ouvrage collectif DOI : 10.53186/1028514 En ligne : https://doi.org/10.53186/1028514 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=102571 Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images / Xiao Li in Cartography and Geographic Information Science, vol 49 n° 1 (January 2022)
[article]
Titre : Urban infrastructure audit: an effective protocol to digitize signalized intersections by mining street view images Type de document : Article/Communication Auteurs : Xiao Li, Auteur ; Huan Ning, Auteur ; Xiao Huang, Auteur ; et al., Auteur Année de publication : 2022 Article en page(s) : pp 32 - 49 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] carrefour
[Termes IGN] cartographie urbaine
[Termes IGN] couche thématique
[Termes IGN] exploration d'images
[Termes IGN] feu de circulation
[Termes IGN] image Streetview
[Termes IGN] Mapillary
[Termes IGN] réseau routier
[Termes IGN] segmentation d'image
[Termes IGN] signalisation routièreRésumé : (auteur) Auditing and mapping traffic infrastructure is a crucial task in urban management. For example, signalized intersections play an essential role in transportation management; however, effectively identifying these intersections remains unsolved. Traditionally, signalized intersection data are manually collected through field audits or checking street view images (SVIs), which is time-consuming and labor-intensive. This study proposes an effective protocol to identify signalized intersections using road networks and SVIs. First, we propose a six-step geoprocessing model to generate an intersection feature layer from road networks. Second, we utilize up to three nearest SVIs to capture streetscapes at each intersection. Then, a deep learning-based image segmentation model is adopted to recognize traffic light-related pixels from each SVI. Last, we design a post-processing step to generate new features characterizing SVIs’ segmentation results at each intersection and build a decision tree model to determine the traffic control type. Results demonstrate that the proposed protocol can effectively identify signalized intersections with an overall accuracy of 97.05%. It also proves the effectiveness of SVIs for auditing urban infrastructures. This study can directly benefit transportation agencies by providing a ready-to-use smart audit and mapping solution for large-scale identification and mapping of signalized intersections. Numéro de notice : A2022-017 Affiliation des auteurs : non IGN Thématique : IMAGERIE/URBANISME Nature : Article DOI : 10.1080/15230406.2021.1992299 Date de publication en ligne : 16/11/2021 En ligne : https://doi.org/10.1080/15230406.2021.1992299 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99148
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Ishalina in Transactions in GIS, vol 25 n° 5 (October 2021)PermalinkSeawater Debye model function at L-band and its impact on salinity retrieval from Aquarius satellite data / Yiwen Zhou in IEEE Transactions on geoscience and remote sensing, vol 59 n° 10 (October 2021)PermalinkSpectral reflectance estimation of UAS multispectral imagery using satellite cross-calibration method / Saket Gowravaram in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 10 (October 2021)PermalinkUnsupervised self-adaptive deep learning classification network based on the optic nerve microsaccade mechanism for unmanned aerial vehicle remote sensing image classification / Ming Cong in Geocarto international, vol 36 n° 18 ([01/10/2021])PermalinkAerial and UAV images for photogrammetric analysis of Belvedere Glacier evolution in the period 1977–2019 / Carlo Lapige De Gaetani in Remote sensing, vol 13 n° 18 (September-2 2021)PermalinkMapping canopy heights in dense tropical forests using low-cost UAV-derived photogrammetric point clouds and machine learning approaches / He Zhang in Remote sensing, vol 13 n° 18 (September-2 2021)PermalinkRecurrent-based regression of Sentinel time series for continuous vegetation monitoring / Anatol Garioud in Remote sensing of environment, vol 263 (15 September 2021)PermalinkAutomatic building detection with polygonizing and attribute extraction from high-resolution images / Samitha Daranagama in ISPRS International journal of geo-information, vol 10 n° 9 (September 2021)PermalinkClassification of tree species in a heterogeneous urban environment using object-based ensemble analysis and World View-2 satellite imagery / Simbarashe Jombo in Applied geomatics, vol 13 n° 3 (September 2021)PermalinkA comparison of ALS and dense photogrammetric point clouds for individual tree detection in radiata pine plantations / Irfan A. Iqbal in Remote sensing, vol 13 n° 17 (September-1 2021)PermalinkConiferous and broad-leaved forest distinguishing using L-band polarimetric SAR data / Fang Shang in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkA deep translation (GAN) based change detection network for optical and SAR remote sensing images / Xinghua Li in ISPRS Journal of photogrammetry and remote sensing, vol 179 (September 2021)PermalinkDetection of aspen in conifer-dominated boreal forests with seasonal multispectral drone image point clouds / Alwin A. Hardenbol in Silva fennica, vol 55 n° 4 (September 2021)PermalinkDetermining optimal photogrammetric adjustment of images obtained from a fixed-wing UAV / Karolina Pargiela in Photogrammetric record, Vol 36 n° 175 (September 2021)PermalinkDevelopment of a GIS-based alert system to mitigate flash flood impacts in Asyut governorate, Egypt / Soha A. Mohamed in Natural Hazards, vol 108 n° 3 (September 2021)PermalinkEstimating regional soil moisture with synergistic use of AMSR2 and MODIS images / Majid Rahimzadegan in Photogrammetric Engineering & Remote Sensing, PERS, vol 87 n° 9 (September 2021)PermalinkGeoglam, l'agriculture par satellite / Laurent Polidori in Géomètre, n° 2194 (septembre 2021)PermalinkHyperspectral image fusion and multitemporal image fusion by joint sparsity / Han Pan in IEEE Transactions on geoscience and remote sensing, Vol 59 n° 9 (September 2021)PermalinkLes journées de la Recherche IGN 2021 / Anonyme in Géomatique expert, n° 135 (septembre 2021)Permalink