Descripteur
Termes descripteurs IGN > imagerie > photographie
photographie
Commentaire :
Document obtenu par une prise de vue avec un appareil photo argentique ou à plaques. Les fichiers numériques obtenus par des caméras numériques sont des images.
|


Etendre la recherche sur niveau(x) vers le bas
Evolution of the beaches in the regional Park of Salinas and Arenales of San Pedro del Pinatar (Southeast of Spain) (1899–2019) / Daniel Ibarra-Marinas in ISPRS International journal of geo-information, vol 10 n° 4 (April 2021)
![]()
[article]
Titre : Evolution of the beaches in the regional Park of Salinas and Arenales of San Pedro del Pinatar (Southeast of Spain) (1899–2019) Type de document : Article/Communication Auteurs : Daniel Ibarra-Marinas, Auteur ; Francisco Belmonte-Serrato, Auteur ; Gustavo A. Ballesteros-Pelegrín, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 200 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes descripteurs IGN] action anthropique
[Termes descripteurs IGN] analyse diachronique
[Termes descripteurs IGN] analyse spatio-temporelle
[Termes descripteurs IGN] cartographie ancienne
[Termes descripteurs IGN] construction
[Termes descripteurs IGN] érosion côtière
[Termes descripteurs IGN] impact sur l'environnement
[Termes descripteurs IGN] Murcie (Espagne)
[Termes descripteurs IGN] photographie aérienne
[Termes descripteurs IGN] plage
[Termes descripteurs IGN] QGIS
[Termes descripteurs IGN] sédiment
[Termes descripteurs IGN] trait de côteRésumé : (auteur) Coastal erosion is an issue which affects beaches all over the world and that signifies enormous economic and environmental losses. Classed as a slow phenomenon, the evolution of the coastline requires long-term analysis. In this study, old cartography and aerial photographs from various dates have been used to study the evolution of the coastline. The information has been processed with free software (QGIS) and for the calculation of sediment transport the Coastal Modeling System (SMC) software. The results show the accretion/erosion phenomena that occurred after the construction of the port in San Pedro del Pinatarin 1954 and which changed the coastal dynamics of a highly protected area. In some sectors, the beach has been reduced almost in its entirety, with retreat rates of up to −2.05 m per year and a total area loss of 66,419.81 m2 in Las Salinas beach and 76,891.13 m2 on Barraca Quemada beach. Numéro de notice : A2021-303 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi10040200 date de publication en ligne : 25/03/2021 En ligne : https://doi.org/10.3390/ijgi10040200 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97423
in ISPRS International journal of geo-information > vol 10 n° 4 (April 2021) . - n° 200[article]
Titre : Remote sensing and GIS Type de document : Guide/Manuel Auteurs : Basudeb Bhatta, Auteur Mention d'édition : 3ème édition Editeur : Oxford, Londres, ... : Oxford University Press Année de publication : 2021 Importance : 752 p. Format : 24 x 18 cm ISBN/ISSN/EAN : 978-0-19-949664-8 Note générale : Bibliographie
additional reading material with Oxford arealLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Télédétection
[Termes descripteurs IGN] acquisition d'images
[Termes descripteurs IGN] airborne multispectral scanner
[Termes descripteurs IGN] analyse spatiale
[Termes descripteurs IGN] Global Navigation Satellite System
[Termes descripteurs IGN] image hyperspectrale
[Termes descripteurs IGN] image thermique
[Termes descripteurs IGN] interféromètrie par radar à antenne synthétique
[Termes descripteurs IGN] Lidar
[Termes descripteurs IGN] modèle numérique de surface
[Termes descripteurs IGN] modèle numérique de terrain
[Termes descripteurs IGN] modélisation 3D
[Termes descripteurs IGN] orthorectification
[Termes descripteurs IGN] Passive and Active L and S band Sensor
[Termes descripteurs IGN] photographie aérienne
[Termes descripteurs IGN] Satellite Microwave Radiometer
[Termes descripteurs IGN] scène 3D
[Termes descripteurs IGN] stéréoscopie
[Termes descripteurs IGN] système d'information géographique
[Termes descripteurs IGN] traitement d'image
[Termes descripteurs IGN] visualisation 3DIndex. décimale : 35.00 Télédétection - généralités Résumé : (Editeur) Beginning with the history and basic concepts of remote sensing and GIS, the book gives an exhaustive coverage of optical, thermal, and microwave remote sensing, global navigation satellite systems (such as GPS and IRNSS), digital photogrammetry, visual image analysis, digital image processing, spatial and attribute data model, geospatial analysis, and planning, implementation, and management of GIS. It also presents the modern trends of remote sensing and GIS with an illustrated discussion on its numerous applications. Note de contenu : 1. Concept of Remote Sensing
1.1 Introduction
1.2 Distance of Remote Sensing
1.3 Definition of Remote Sensing
1.4 Remote Sensing: Art and/or Science
1.5 Data
1.6 Remote Sensing Process
1.7 Source of Energy
1.8 Interaction with Atmosphere
1.9 Interaction with Target
1.9.1 Hemispherical Absorptance, Transmittance, and Reflectan
1.10 Interaction with the Atmosphere Again
1.11 Recording of Energy by Sensor
1.12 Transmission, Reception, and Processing
1.13 Interpretation and Analysis
1.14 Applications of Remote Sensing
1.15 Advantages of Remote Sensing
1.16 Limitations of Remote Sensing
1.17 Ideal Remote Sensing System
2. Types of Remote Sensing and Sensor Characteristics
2.1 Introduction
2.2 Types of Remote Sensing
2.3 Characteristics of Images
2.4 Orbital Characteristics of Satellite
2.5 Remote Sensing Satellites
2.6 Concept of Swath
2.7 Concept of Nadir
2.8 Sensor Resolutions
2.9 Image Referencing System
2.9.1 Path
2.9.2 Row
2.9.3 Orbital Calendar
3. History of Remote Sensing and Indian Space Program
3.1 Introduction
3.2 The Early Age
3.3 The Middle Age
3.4 The Modern Age or Space Age
3.5 Indian Space Program
4. Photographic Imaging
4.1 Introduction
4.2 Camera Systems
4.3 Types of Camera
4.4 Filter
4.5 Film
4.6 Geometry of Aerial Photography
4.7 Ideal Time and Atmosphere for Aerial Remote Sensing
5. Digital Imaging
5.1 Introduction
5.2 Digital Image
5.3 Sensor
5.4 Imaging by Scanning Technique
5.5 Hyper-spectral Imaging
5.6 Imaging By Non-scanning Technique
5.7 Thermal Remote Sensing
5.8 Other Sensors
6. Microwave Remote Sensing
6.1 Introduction
6.2 Passive Microwave Remote Sensing
6.3 Active Microwave Remote Sensing
6.4 Radar Imaging
6.5 Airborne Versus Space-Borne Radars
6.6 Radar Systems
7. Ground-truth Data and Global Positioning System
7.1 Introduction
7.2 Requirements of Ground-Truth Data
7.3 Instruments for Ground Truthing
7.4 Parameters of Ground Truthing
7.5 Factors of Spectral Measurement
7.6 Global Navigation Satellite System
8. Photogrammetry
8.1 Introduction
8.2 Development of Photogrammetry
8.3 Classification of Photogrammetry
8.4 Photogrammetric Process
8.5 Acquisition of Imagery and its Support Data
8.6 Orientation and Triangulation
8.7 Stereo Model Compilation
8.8 Stereoscopic 3D Viewing
8.9 Stereoscopic Measurement
8.10 DTM/DEM Generation
8.11 Contour Map Generation
8.12 Orthorectification
8.13 3D Feature Extraction
8.14 3D Scene Modelling
8.15 Photogrammetry and LiDAR
8.16 Radargrammetry and Radar Interferometry
8.17 Limitations of Photogrammetry
9. Visual Image Interpretation
9.1 Introduction
9.2 Information Extraction by Human and Computer
9.3 Remote Sensing Data Products
9.4 Border or Marginal Information
9.5 Image Interpretation
9.6 Elements of Visual Image Interpretation
9.7 Interpretation Keys
9.8 Generation of Thematic Maps
9.9 Thermal Image Interpretation
9.10 Radar Image Interpretation
10. Digital Image Processing
10.1 Introduction
10.2 Categorization of Image Processing
10.3 Image Processing Systems
10.4 Digital Image
10.5 Media for Digital Data Recording, Storage, and Distribution
10.6 Data Formats of Digital Image
10.7 Header Information
10.8 Display of Digital Image
10.9 Pre-processing
10.10 Image Enhancement
10.11 Image Transformation
10.12 Image Classification
11. Data Integration, Analysis, and Presentation
11.1 Introduction
11.2 Multi-approach of Remote Sensing
11.3 Integration with Ground Truth and Other Ancillary Data
11.4 Integration of Transformed Data
11.5 Integration with GIS
11.6 Process of Remote Sensing Data Analysis
11.7 The Level of Detail
11.8 Limitations of Remote Sensing Data Analysis
11.9 Presentation
12. Applications of Remote Sensing
12.1 Introduction
12.2 Land Cover and Land Use
12.3 Agriculture
12.4 Forestry
12.5 Geology
12.6 Geomorphology
12.7 Urban Applications
12.8 Hydrology
12.9 Mapping
12.10 Oceans and Coastal Monitoring
12.11 Monitoring of Atmospheric Constituents
PART II Geographic Information Systems and Geospatial Analysis
13. Concept of Geographic Information Systems
13.1 Introduction
13.2 Definitions of GIS
13.3 Key Components of GIS
13.4 GIS-An Integration of Spatial and Attribute Information
13.5 GIS-Three Views of Information System
13.6 GIS and Related Terms
13.7 GIS-A Knowledge Hub
13.8 GIS-A Set of Interrelated Subsystems
13.9 GIS-An Information Infrastructure
13.10 Origin of GIS
14. Functions and Advantages of GIS
14.1 Introduction
14.2 Functions of GIS
14.3 Application Areas of GIS
14.4 Advantages of GIS
14.5 Functional Requirements of GIS
14.6 Limitations of GIS
15. Spatial Data Model
15.1 Introduction
15.2 Spatial, Thematic, and Temporal Dimensions of Geographic Data
15.3 Spatial Entity and Object
15.4 Spatial Data Model
15.5 Raster Data Model
15.6 Vector Data Model
15.7 Raster versus Vector
15.8 Object-Oriented Data Model
15.9 File Formats of Spatial Data
16. Attribute Data Management and Metadata Concept
16.1 Introduction
16.2 Concept of Database and DBMS
16.3 Advantages of DBMS
16.4 Functions of DBMS
16.5 File and Data Access
16.6 Data Models
16.7 Database Models
16.8 Data Models in GIS
16.9 Concept of SQL
16.10 Concept of Metadata
17. Process of GIS
17.1 Introduction
17.2 Data Capture
17.3 Data Sources
17.4 Data Encoding Methods
17.5 Linking of Spatial and Attribute Data
17.6 Organizing Data for Analysis
18. Geospatial Analysis
18.1 Introduction
18.2 Geospatial Data Analysis
18.3 Integration and Modelling of Spatial Data
18.4 Geospatial Data Analysis Methods
18.5 Database Query
18.6 Geospatial Measurements
18.7 Overlay Operations
18.8 Network Analysis
18.9 Surface Analysis
18.10 Geostatistics
18.11 Geovisualization
19. Planning, Implementation, and Management of GIS
19.1 Introduction
19.2 Planning of Project
19.3 Implementation of Project
19.4 Management of Project
19.5 Keys for Successful GIS
19.6 Reasons for Unsuccessful GIS
20. Modern Trends of GIS
20.1 Introduction
20.2 Local to Global Concept in GIS
20.3 Increase in Dimensions in GIS
20.4 Linear to Non-linear Techniques in GIS
20.5 Development in Relation between Geometry and Algebra in GIS
20.6 Development of Common Techniques in GIS
20.7 Integration of GIS and Remote Sensing
20.8 Integration of GIS and Multimedia
20.9 3D GIS
20.9.1 Virtual Reality in GIS
20.10 Integration of 3D GIS and Web GIS
20.11 4D GIS and Real-time GIS
20.12 Mobile GIS
20.12.1 Mobile mapping
20.13 Collaborative GIS (CGIS)
21. Change Detection and Geosimulation
21.1 Visual change detection
21.2 Thresholding
21.3 Image difference
21.4 Image regression
21.5 Image ratioing
21.6 Vegetation index differencing
21.7 Principal component differencing
21.8 Multi-temporal image stock classification
21.9 Post classification comparison
21.10 Change vector analysis
21.12 Cellular automata simulation
21.13 Multi-agent simulation
21.14 ANN learning in simulation
Appendix A - Concept of Map, Coordinate System, and Projection
Appendix B - Concept on Mathematical TopicsNuméro de notice : 26518 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/IMAGERIE/POSITIONNEMENT Nature : Manuel de cours DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97342 Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 26518-01 35.00 Livre Centre de documentation Télédétection Disponible Structure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring / Edoardo Grottoli in Remote sensing, vol 13 n° 1 (January 2021)
![]()
[article]
Titre : Structure-from-motion-derived digital surface models from historical aerial photographs: A new 3D application for coastal dune monitoring Type de document : Article/Communication Auteurs : Edoardo Grottoli, Auteur ; Mélanie Biausque, Auteur ; David Rogers, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : n° 95 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes descripteurs IGN] analyse diachronique
[Termes descripteurs IGN] carte de profondeur
[Termes descripteurs IGN] données lidar
[Termes descripteurs IGN] dune
[Termes descripteurs IGN] érosion côtière
[Termes descripteurs IGN] filtrage de points
[Termes descripteurs IGN] image captée par drone
[Termes descripteurs IGN] modèle numérique de surface
[Termes descripteurs IGN] photographie numérisée
[Termes descripteurs IGN] reconstruction 3D
[Termes descripteurs IGN] semis de points
[Termes descripteurs IGN] structure-from-motion
[Termes descripteurs IGN] surveillance du littoralRésumé : (auteur) Recent advances in structure-from-motion (SfM) techniques have proliferated the use of unmanned aerial vehicles (UAVs) in the monitoring of coastal landform changes, particularly when applied in the reconstruction of 3D surface models from historical aerial photographs. Here, we explore a number of depth map filtering and point cloud cleaning methods using the commercial software Agisoft Metashape Pro to determine the optimal methodology to build reliable digital surface models (DSMs). Twelve different aerial photography-derived DSMs are validated and compared against light detection and ranging (LiDAR)- and UAV-derived DSMs of a vegetated coastal dune system that has undergone several decades of coastline retreat. The different studied methods showed an average vertical error (root mean square error, RMSE) of approximately 1 m, with the best method resulting in an error value of 0.93 m. In our case, the best method resulted from the removal of confidence values in the range of 0–3 from the dense point cloud (DPC), with no filter applied to the depth maps. Differences among the methods examined were associated with the reconstruction of the dune slipface. The application of the modern SfM methodology to the analysis of historical aerial (vertical) photography is a novel (and reliable) new approach that can be used to better quantify coastal dune volume changes. DSMs derived from suitable historical aerial photographs, therefore, represent dependable sources of 3D data that can be used to better analyse long-term geomorphic changes in coastal dune areas that have undergone retreat. Numéro de notice : A2021-079 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/rs13010095 date de publication en ligne : 30/12/2020 En ligne : https://doi.org/10.3390/rs13010095 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96821
in Remote sensing > vol 13 n° 1 (January 2021) . - n° 95[article]Geometric distortion of historical images for 3D visualization / Evelyn Paiz-Reyes in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, V-2 (August 2020)
![]()
[article]
Titre : Geometric distortion of historical images for 3D visualization Type de document : Article/Communication Auteurs : Evelyn Paiz-Reyes , Auteur ; Mathieu Brédif
, Auteur ; Sidonie Christophe
, Auteur
Année de publication : 2020 Projets : Alegoria / Gouet-Brunet, Valérie 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 649 - 655 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes descripteurs IGN] base de données historiques
[Termes descripteurs IGN] distorsion d'image
[Termes descripteurs IGN] modèle de déformation des images
[Termes descripteurs IGN] photographie numérisée
[Termes descripteurs IGN] rendu (géovisualisation)
[Termes descripteurs IGN] scène 3D
[Termes descripteurs IGN] visualisation 3D
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) Archivists, historians and national mapping agencies, among others, are archiving large datasets of historical photographs. Nevertheless, the capturing devices used to acquire these images possessed a diversity of effects that influenced the quality of the final resulting picture, e.g. geometric distortion, chromatic aberration, depth of field variation, etc. This paper examines singularly the topic of geometric distortion for a co-visualization of historical photos within a 3D model of the photographed scene. A distortion function of an image is ordinarily estimated only on the image domain by adjusting its parameters to observations of point correspondences. This mathematical function may exhibit overfits, oscillations or may not be well defined outside of this domain. The contribution of this work is the description of a distortion model defined on the whole undistorted image plane. We extrapolate the distortion estimated only on the image domain and then transfer this distortion information to the view of the 3D scene. This enables to look at the scene through an estimated camera and zoom out to see the context around the original photograph with a well-defined and behaved distortion. These findings may be a significant addition to the overall purpose of creating innovative ways to examine and visualize old photographs. Numéro de notice : A2020-468 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-2-2020-649-2020 date de publication en ligne : 03/08/2020 En ligne : https://doi.org/10.5194/isprs-annals-V-2-2020-649-2020 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95537
in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences > V-2 (August 2020) . - pp 649 - 655[article]
[article]
Titre : Experte image aérienne... Type de document : Article/Communication Auteurs : Laurent Polidori, Auteur Année de publication : 2020 Article en page(s) : pp 44 - 45 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes descripteurs IGN] analyse comparative
[Termes descripteurs IGN] données spatiotemporelles
[Termes descripteurs IGN] photographie aérienneRésumé : (Auteur) L'avantage des photographies aériennes par rapport à de simples mesures est qu'au-delà des amplitudes de déplacements, elles permettent d'en comprendre la nature et ainsi d'éclairer pleinement l'expertise. Numéro de notice : A2020-179 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94847
in Géomètre > n° 2179 (avril 2020) . - pp 44 - 45[article]Réservation
Réserver ce documentExemplaires (1)
Code-barres Cote Support Localisation Section Disponibilité 063-2020041 SL Revue Centre de documentation Revues en salle Disponible 10th Colour and Visual Computing Symposium 2020 (CVCS 2020), Gjøvik, Norway, and Virtual, September 16-17, 2020 / Jean-Baptiste Thomas (2020)
PermalinkPermalinkCamera orientation, calibration and inverse perspective with uncertainties: a Bayesian method applied to area estimation from diverse photographs / Grégoire Guillet in ISPRS Journal of photogrammetry and remote sensing, vol 159 (January 2020)
PermalinkPotential of UAV photogrammetry for characterization of forest canopy structure in uneven-aged mixed conifer–broadleaf forests / Sadeepa Jayathunga in International Journal of Remote Sensing IJRS, vol 41 n° 1 (01 - 08 janvier 2020)
PermalinkTowards new applications of underwater photogrammetry for investigating coral reef morphology and habitat complexity in the Myeik Archipelago, Myanmar / Martina Anelli in Geocarto international, vol 34 n° 5 ([01/05/2019])
PermalinkPermalinkArchival aerial photogrammetric surveys, a data source to study land use/cover evolution over the last century : opportunities and issues / Arnaud Le Bris (2019)
PermalinkPermalinkForest inventory sensitivity to UAS-based image processing algorithms / Bonifasius Maturbongs in Annals of forest research, vol 62 n° 1 (January - June 2019)
PermalinkPermalinkPermalinkHow to calibrate historical aerial photographs : a change analysis of naturally dynamic boreal forest landscapes / Niko Kulha in Forests, vol 9 n° 10 (October 2018)
PermalinkPrecise DEM extraction from Svalbard using 1936 high oblique imagery / Luc Girod in Geoscientific instrumentation methods and data systems, vol 7 n° 4 ([01/10/2018])
![]()
PermalinkVers une remise en géométrie automatique des prises de vue aériennes historiques photogrammétriques / Arnaud Le Bris in Revue Française de Photogrammétrie et de Télédétection, n° 217-218 (juin - septembre 2018)
PermalinkGenerating terrestrial glacier views from historic airphotos for comparison with contemporary ground photographs / Marion Holst (2018)
PermalinkPermalinkPermalinkAgricultural cropland mapping using black-and-white aerial photography, Object-Based Image Analysis and Random Forests / M.F.A. Vogels in International journal of applied Earth observation and geoinformation, vol 54 (February 2017)
PermalinkCombination of image descriptors for the exploration of cultural photographic collections / Neelanjan Bhowmik in Journal of Electronic Imaging, vol 26 n° 1 (January - February 2017)
PermalinkRelevé topographique des environnements urbains [article originellement paru dans le numéro mai/juin 2016 de la revue italienne GEOMedia] / Luigi Colombo in Géomatique expert, n° 113 (novembre - décembre 2016)
Permalink