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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Remote Sensing Technology Applications in Forestry and REDD+
Type de document :	Monographie
Auteurs :	Kim Calders, Editeur scientifique ; Inge Jonckheere, Editeur scientifique ; Mikko Vastaranta, Editeur scientifique ; Joanne Nightingale, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2020
Importance :	244 p.
ISBN/ISSN/EAN :	978-3-03928-471-9
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] canopée [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] déboisement [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image multibande [Termes descripteurs IGN] image Sentinel [Termes descripteurs IGN] Pinus massoniana [Termes descripteurs IGN] polarimétrie radar [Termes descripteurs IGN] télémétrie laser aéroporté [Termes descripteurs IGN] télémétrie laser terrestre
Résumé :	(Editeur) Advances in close-range and remote sensing technologies are driving innovations in forest resource assessments and monitoring on varying scales. Data acquired with airborne and spaceborne platforms provide high(er) spatial resolution, more frequent coverage, and more spectral information. Recent developments in ground-based sensors have advanced 3D measurements, low-cost permanent systems, and community-based monitoring of forests. The UNFCCC REDD+ mechanism has advanced the remote sensing community and the development of forest geospatial products that can be used by countries for the international reporting and national forest monitoring. However, an urgent need remains to better understand the options and limitations of remote and close-range sensing techniques in the field of forest degradation and forest change. Therefore, we invite scientists working on remote sensing technologies, close-range sensing, and field data to contribute to this Special Issue. Topics of interest include: (1) novel remote sensing applications that can meet the needs of forest resource information and REDD+ MRV, (2) case studies of applying remote sensing data for REDD+ MRV, (3) timeseries algorithms and methodologies for forest resource assessment on different spatial scales varying from the tree to the national level, and (4) novel close-range sensing applications that can support sustainable forestry and REDD+ MRV. We particularly welcome submissions on data fusion.
Numéro de notice :	26296
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Monographie
DOI :	10.3390/books978-3-03928-471-9
date de publication en ligne :	07/04/2020
En ligne :	https://doi.org/10.3390/books978-3-03928-471-9
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95009

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Applications of photogrammetry for environmental research
Type de document :	Monographie
Auteurs :	Francesco Mancini, Editeur scientifique ; Riccardo Salvini, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2020
Importance :	154 p.
ISBN/ISSN/EAN :	978-3-03928-181-7
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications photogrammétriques [Termes descripteurs IGN] hauteur des arbres [Termes descripteurs IGN] image satellite [Termes descripteurs IGN] photographie aérienne [Termes descripteurs IGN] populus (genre) [Termes descripteurs IGN] risque environnemental
Résumé :	(Editeur) The book presents a collection of papers focused on recent progress in key areas of photogrammetry for environmental research. Applications oriented to the understanding of natural phenomena and quantitative processes using dataset from photogrammetry (from satellite to unmanned aerial vehicle images) and terrestrial laser scanning, also by a diachronic approach, are reported. The book covers topics of interest of many disciplines from geography, geomorphology, engineering geology, geotechnology, including landscape description and coastal studies. Mains issues faced by the book are related to applications on coastal monitoring, using multitemporal aerial images, and investigations on geomorphological hazard by the joint use of proximal photogrammetry, terrestrial and aerial laser scanning aimed to the reconstruction of detailed surface topography and successive 2D/3D numerical simulations for rock slope stability analyses. Results reported in the book bring into evidence the fundamental role of multitemporal surveys and reliable reconstruction of morphologies from photogrammetry and laser scanning as support to environmental researches.
Numéro de notice :	26302
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Monographie
DOI :	10.3390/books978-3-03928-181-7
date de publication en ligne :	30/01/2020
En ligne :	https://doi.org/10.3390/books978-3-03928-181-7
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95035

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Applied and computational statistics
Type de document :	Monographie
Auteurs :	Sorana D. Bolboacă, Auteur
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2020
Importance :	104 p.
ISBN/ISSN/EAN :	978-3-03928-177-0
Note générale :	Bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Statistiques [Termes descripteurs IGN] méthode de Monte-Carlo [Termes descripteurs IGN] méthode du maximum de vraisemblance (estimation) [Termes descripteurs IGN] probabilité
Résumé :	(Editeur) Research without statistics is like water in the sand; the latter is necessary to reap the benefits of the former. This collection of articles is designed to bring together different approaches to applied statistics. The studies presented in this book are a tiny piece of what applied statistics means and how statistical methods find their usefulness in different fields of research from theoretical frames to practical applications such as genetics, computational chemistry, and experimental design. This book presents several applications of the statistics: A new continuous distribution with five parameters—the modified beta Gompertz distribution; A method to calculate the p-value associated with the Anderson–Darling statistic; An approach of repeated measurement designs; A validated model to predict statement mutations score; A new family of structural descriptors, called the extending characteristic polynomial (EChP) family, used to express the link between the structure of a compound and its properties. This collection brings together authors from Europe and Asia with a specific contribution to the knowledge in regards to theoretical and applied statistics.
Note de contenu :	- The Modiﬁed Beta Gompertz Distribution: Theory and Applications - Computation of Probability Associated with Anderson–Darling Statistic - Optimal Repeated Measurements for Two Treatment Designs with Dependent Observations: The Case of Compound Symmetry - A Model for Predicting Statement Mutation Scores - Extending the Characteristic Polynomial for Characterization of C20 Fullerene Congeners
Numéro de notice :	26298
Affiliation des auteurs :	non IGN
Thématique :	MATHEMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03928-177-0
date de publication en ligne :	30/01/2020
En ligne :	https://doi.org/10.3390/books978-3-03928-177-0
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95014

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Automated machine learning : methods, systems, challenges
Type de document :	Monographie
Auteurs :	Frank Hutter, Editeur scientifique ; Lars Kotthoff, Editeur scientifique ; Joaquin Vanschoren, Editeur scientifique
Editeur :	Springer Nature
Année de publication :	2019
Collection :	The Springer Series on Challenges in Machine Learning SSCML, ISSN 2520-1328
Importance :	219 p.
ISBN/ISSN/EAN :	978-3-030-05318-5
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Intelligence artificielle [Termes descripteurs IGN] algorithme d'apprentissage [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] optimisation (mathématiques)
Index. décimale :	26.40 Intelligence artificielle
Résumé :	(Editeur) This open access book presents the first comprehensive overview of general methods in Automated Machine Learning (AutoML), collects descriptions of existing systems based on these methods, and discusses the first series of international challenges of AutoML systems. The recent success of commercial ML applications and the rapid growth of the field has created a high demand for off-the-shelf ML methods that can be used easily and without expert knowledge. However, many of the recent machine learning successes crucially rely on human experts, who manually select appropriate ML architectures (deep learning architectures or more traditional ML workflows) and their hyperparameters. To overcome this problem, the field of AutoML targets a progressive automation of machine learning, based on principles from optimization and machine learning itself. This book serves as a point of entry into this quickly-developing field for researchers and advanced students alike, as well as providing a reference for practitioners aiming to use AutoML in their work.
Note de contenu :	AUTOML METHODS - Hyperparameter Optimization - Meta-Learning - Neural Architecture Search AUTOML SYSTEMS - Auto-WEKA: Automatic Model Selection and Hyperparameter Optimization in WEKA - Hyperopt-Sklearn - Auto-sklearn: Efficient and Robust Automated Machine Learning - Towards Automatically-Tuned Deep Neural Networks - TPOT: A Tree-Based Pipeline Optimization Tool for Automating Machine Learning - The Automatic Statistician AUTOML CHALLENGES - Analysis of the AutoML Challenge Series 2015–2018 - Correction to: Neural Architecture Search
Numéro de notice :	26299
Affiliation des auteurs :	non IGN
Thématique :	INFORMATIQUE/MATHEMATIQUE
Nature :	Monographie
DOI :	10.1007%2F978-3-030-05318-5
date de publication en ligne :	04/02/2020
En ligne :	https://link.springer.com/book/10.1007%2F978-3-030-05318-5
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95032

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre de série :	Learning to Understand Remote Sensing Images, 1
Titre :	Volume 1
Type de document :	Monographie
Auteurs :	Qi Wang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	426 p.
ISBN/ISSN/EAN :	978-3-03897-685-1
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] réseau neuronal convolutif
Résumé :	(Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Numéro de notice :	26301A
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-685-1
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-685-1
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95033

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Learning to Understand Remote Sensing Images, 2. Volume 2 / Qi Wang (2019)

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre de série :	Learning to Understand Remote Sensing Images, 2
Titre :	Volume 2
Type de document :	Monographie
Auteurs :	Qi Wang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	376 p.
ISBN/ISSN/EAN :	978-3-03897-699-8
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] réseau neuronal convolutif
Résumé :	(Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Numéro de notice :	26301B
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-699-8
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-699-8
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95034

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Public

contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre de série :	Learning to Understand Remote Sensing Images, 2
Titre :	Volume 2
Type de document :	Monographie
Auteurs :	Qi Wang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	376 p.
ISBN/ISSN/EAN :	978-3-03897-699-8
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] réseau neuronal convolutif
Résumé :	(Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Numéro de notice :	26301B
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-699-8
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-699-8
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95034

Voir aussi

Learning to Understand Remote Sensing Images, 1. Volume 1 / Qi Wang (2019)

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre de série :	Learning to Understand Remote Sensing Images, 1
Titre :	Volume 1
Type de document :	Monographie
Auteurs :	Qi Wang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	426 p.
ISBN/ISSN/EAN :	978-3-03897-685-1
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image mixte [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] apprentissage semi-dirigé [Termes descripteurs IGN] fusion d'images [Termes descripteurs IGN] image hyperspectrale [Termes descripteurs IGN] image Landsat [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] réseau neuronal convolutif
Résumé :	(Editeur) With the recent advances in remote sensing technologies for Earth observation, many different remote sensors are collecting data with distinctive properties. The obtained data are so large and complex that analyzing them manually becomes impractical or even impossible. Therefore, understanding remote sensing images effectively, in connection with physics, has been the primary concern of the remote sensing research community in recent years. For this purpose, machine learning is thought to be a promising technique because it can make the system learn to improve itself. With this distinctive characteristic, the algorithms will be more adaptive, automatic, and intelligent. This book introduces some of the most challenging issues of machine learning in the field of remote sensing, and the latest advanced technologies developed for different applications. It integrates with multi-source/multi-temporal/multi-scale data, and mainly focuses on learning to understand remote sensing images. Particularly, it presents many more effective techniques based on the popular concepts of deep learning and big data to reach new heights of data understanding. Through reporting recent advances in the machine learning approaches towards analyzing and understanding remote sensing images, this book can help readers become more familiar with knowledge frontier and foster an increased interest in this field.
Numéro de notice :	26301A
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE/INFORMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-685-1
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-685-1
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95033

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Geoinformatics in citizen science
Type de document :	Monographie
Auteurs :	Gloria Bordogna, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	206 p.
ISBN/ISSN/EAN :	978-3-03921-073-2
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Géomatique web [Termes descripteurs IGN] analyse de données [Termes descripteurs IGN] cartographie thématique [Termes descripteurs IGN] données localisées des bénévoles [Termes descripteurs IGN] OpenStreetMap [Termes descripteurs IGN] QGIS [Termes descripteurs IGN] qualité des données [Termes descripteurs IGN] système d'information géographique
Résumé :	(Editeur) The book features contributions that report original research in the theoretical, technological, and social aspects of geoinformation methods, as applied to supporting citizen science. Specifically, the book focuses on the technological aspects of the field and their application toward the recruitment of volunteers and the collection, management, and analysis of geotagged information to support volunteer involvement in scientific projects. Internationally renowned research groups share research in three areas: First, the key methods of geoinformatics within citizen science initiatives to support scientists in discovering new knowledge in specific application domains or in performing relevant activities, such as reliable geodata filtering, management, analysis, synthesis, sharing, and visualization; second, the critical aspects of citizen science initiatives that call for emerging or novel approaches of geoinformatics to acquire and handle geoinformation; and third, novel geoinformatics research that could serve in support of citizen science.
Numéro de notice :	26303
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE
Nature :	Monographie
DOI :	10.3390/books978-3-03921-073-2
date de publication en ligne :	28/08/2019
En ligne :	https://doi.org/10.3390/books978-3-03921-073-2
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95045

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Titre :	Satellite altimetry for earth sciences
Type de document :	Monographie
Auteurs :	Frédéric Frappart, Editeur scientifique ; Ole Andersen, Editeur scientifique ; Sergey Lebedev, Editeur scientifique ; Guillaume Ramillien, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	484 p.
ISBN/ISSN/EAN :	978-3-03897-681-3
Note générale :	Bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image radar et applications [Termes descripteurs IGN] altimétrie satellitaire par radar [Termes descripteurs IGN] bande K [Termes descripteurs IGN] classification non dirigée [Termes descripteurs IGN] données GRACE [Termes descripteurs IGN] image Cryosat [Termes descripteurs IGN] image Envisat-ASAR [Termes descripteurs IGN] image Sentinel-3 [Termes descripteurs IGN] niveau de l'eau [Termes descripteurs IGN] océanographie spatiale [Termes descripteurs IGN] série temporelle
Résumé :	(Editeur) Satellite altimetry is a radar technique for measuring the topography of the Earth’s surface. It was initially designed for measuring the ocean’s topography, with reference to an ellipsoid, and for the determination of the marine geoid. Satellite altimetry has provided extremely valuable information on ocean science (e.g., circulation surface geostrophic currents, eddy structures, wave heights, and the propagation of oceanic Kelvin and Rossby waves). With more than 25 years of observations, it is also becoming vital to climate research, providing accurate measurements of sea level variations from regional to global scales. Altimetry has also demonstrated a strong potential for geophysical, cryospheric, and hydrological research and is now commonly used for the monitoring of Arctic and Antarctic ice sheet topography and of terrestrial surface water levels. This book aims to present reviews and recent advances of general interest in the use of radar altimetry in Earth sciences. Manuscripts are related to any aspect of radar altimetry technique or geophysical applications. We also encourage manuscripts resulting from the application of new altimetric technology (SAR, SARin, and Ka band) and improvements expected from missions to be launched in the near future (i.e., SWOT).
Numéro de notice :	26304
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-681-3
date de publication en ligne :	28/08/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-681-3
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95062

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Ten years of TerraSAR-X : scientific results
Type de document :	Monographie
Auteurs :	Michael Eineder, Editeur scientifique ; Achim Roth, Editeur scientifique ; Alberto Moreira, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	422 p.
ISBN/ISSN/EAN :	978-3-03897-725-4
Note générale :	This book is a printed edition of the Special Issue Ten Years of TerraSAR-X—Scientific Results that was published in the open journal "Remote Sensing" from 2018 to 2019.
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Télédétection [Termes descripteurs IGN] image radar moirée [Termes descripteurs IGN] image TerraSAR-X [Termes descripteurs IGN] interféromètrie par radar à antenne synthétique [Termes descripteurs IGN] MNS TerraSAR & TanDEM-X [Termes descripteurs IGN] radar à antenne synthétique [Termes descripteurs IGN] télédétection en hyperfréquence [Termes descripteurs IGN] TerraSAR-X
Résumé :	(Editeur) This Special Issue is a collection of papers addressing the scientific use of data acquired in the course of the TerraSAR-X mission 10 years after launch. The articles deal with the mission itself, the accuracy of the products, with differential interferometry, and with applications in the domains cryosphere, oceans, wetlands, and urban areas.
Numéro de notice :	26042
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Monographie
DOI :	10.3390/books978-3-03897-725-4
date de publication en ligne :	25/04/2019
En ligne :	https://doi.org/10.3390/books978-3-03897-725-4
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=93611

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Titre :	Remote sensing based building extraction
Type de document :	Monographie
Auteurs :	Mohammad Awrangjeb, Auteur ; Xiangyun Hu, Auteur ; Bisheng Yang, Auteur ; Jiaojiao Tian, Auteur
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2020
Importance :	442 p.
ISBN/ISSN/EAN :	978-3-03928-383-5
Note générale :	Bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] apprentissage profond [Termes descripteurs IGN] détection du bâti [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] reconstruction 3D du bâti [Termes descripteurs IGN] réseau neuronal convolutif [Termes descripteurs IGN] segmentation sémantique [Termes descripteurs IGN] semis de points
Résumé :	(Editeur) Building extraction from remote sensing data plays an important role in urban planning, disaster management, navigation, updating geographic databases, and several other geospatial applications. Even though significant research has been carried out for more than two decades, the success of automatic building extraction and modeling is still largely impeded by scene complexity, incomplete cue extraction, and sensor dependency of data. Most recently, deep neural networks (DNN) have been widely applied for high classification accuracy in various areas including land-cover and land-use classification. Therefore, intelligent and innovative algorithms are needed for the success of automatic building extraction and modeling. This Special Issue focuses on newly developed methods for classification and feature extraction from remote sensing data for automatic building extraction and 3D.
Numéro de notice :	26305
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Monographie
DOI :	10.3390/books978-3-03928-383-5
date de publication en ligne :	07/04/2020
En ligne :	https://doi.org/10.3390/books978-3-03928-383-5
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95064

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Visual Sensors
Type de document :	Monographie
Auteurs :	Luis Payá, Editeur scientifique ; Oscar Reinoso Garcia, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2020
Importance :	738 p.
ISBN/ISSN/EAN :	978-3-03928-339-2
Note générale :	Bibliographie
Langues :	Anglais (eng)
Résumé :	(Editeur) Visual sensors are able to capture a large quantity of information from the environment around them. A wide variety of visual systems can be found, from the classical monocular systems to omnidirectional, RGB-D, and more sophisticated 3D systems. Every configuration presents some specific characteristics that make them useful for solving different problems. Their range of applications is wide and varied, including robotics, industry, agriculture, quality control, visual inspection, surveillance, autonomous driving, and navigation aid systems. In this book, several problems that employ visual sensors are presented. Among them, we highlight visual SLAM, image retrieval, manipulation, calibration, object recognition, navigation, etc.
Numéro de notice :	26309
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Monographie
DOI :	10.3390/books978-3-03928-339-2
date de publication en ligne :	07/04/2020
En ligne :	https://doi.org/10.3390/books978-3-03928-339-2
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95067

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Very High Resolution (VHR) satellite imagery : processing and applications
Type de document :	Monographie
Auteurs :	Francisco Eugenio, Editeur scientifique ; Javier Marcello, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	262 p.
ISBN/ISSN/EAN :	978-3-03921-757-1
Note générale :	Bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] analyse texturale [Termes descripteurs IGN] détection du bâti [Termes descripteurs IGN] forêt alpestre [Termes descripteurs IGN] image à très haute résolution [Termes descripteurs IGN] image Pléiades [Termes descripteurs IGN] image Quickbird [Termes descripteurs IGN] image Worldview [Termes descripteurs IGN] risque naturel [Termes descripteurs IGN] traitement d'image
Résumé :	(Editeur) Recently, growing interest in the use of remote sensing imagery has appeared to provide synoptic maps of water quality parameters in coastal and inner water ecosystems;, monitoring of complex land ecosystems for biodiversity conservation; precision agriculture for the management of soils, crops, and pests; urban planning; disaster monitoring, etc. However, for these maps to achieve their full potential, it is important to engage in periodic monitoring and analysis of multi-temporal changes. In this context, very high resolution (VHR) satellite-based optical, infrared, and radar imaging instruments provide reliable information to implement spatially-based conservation actions. Moreover, they enable observations of parameters of our environment at greater broader spatial and finer temporal scales than those allowed through field observation alone. In this sense, recent very high resolution satellite technologies and image processing algorithms present the opportunity to develop quantitative techniques that have the potential to improve upon traditional techniques in terms of cost, mapping fidelity, and objectivity. Typical applications include multi-temporal classification, recognition and tracking of specific patterns, multisensor data fusion, analysis of land/marine ecosystem processes and environment monitoring, etc. This book aims to collect new developments, methodologies, and applications of very high resolution satellite data for remote sensing. The works selected provide to the research community the most recent advances on all aspects of VHR satellite remote sensing.
Numéro de notice :	26310
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Numéro de périodique
DOI :	10.3390/books978-3-03921-757-1
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03921-757-1
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95071

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Satellite information classification and interpretation
Type de document :	Monographie
Auteurs :	Rustam B. Rustamov, Editeur scientifique
Editeur :	London [UK] : IntechOpen
Année de publication :	2019
Importance :	172 p.
ISBN/ISSN/EAN :	978-1-83880-793-1
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Traitement d'image [Termes descripteurs IGN] classification par séparateurs à vaste marge [Termes descripteurs IGN] détection du bâti [Termes descripteurs IGN] image à haute résolution [Termes descripteurs IGN] image proche infrarouge [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] télédétection spatiale
Résumé :	(Editeur) Without a doubt, understanding what we must do to save our home, our planet, and how we are to do it is of the gravest importance for the present generation and the next. Clearly, advances won through space technology and applications of the same to the study of Earth play an excellent and vital role in classification and interpretation of the processes taking place on the Earth and in space. Today, space technology helps us understand Earth and how we can support and manage its state, to keep it in working condition under the current circumstances.How can we do this? Obviously, we must use appropriate methods and instruments to collect the information we need. In the meantime, it is necessary to develop systems to analyze and process the data collected.
Note de contenu :	1. Introductory Chapter: Aerospace Information Classification 2. Pan-sharpening Using Spatial-frequency Method 3. Lossy Compression of Remote Sensing Images with Controllable Distortions 4. Reverse Satellite Transionospheric Sounding: Advantages and Prospects 5. High-Resolution Satellite Imagery Classification for Urban Form Detection 6. Water Management in Irrigation Systems by Using Satellite Information 7. Validation of Satellite (TMPA and IMERG) Rainfall Products with the IMD Gridded Data Sets over Monsoon Core Region of India 8. Near- and Middle-Infrared Monitoring of Burned Areas from Space 9. The Use of Visible Geostationary Operational Meteorological Satellite Imagery in Mapping the Water Balance over Puerto Rico for Water Resource Management
Numéro de notice :	26311
Affiliation des auteurs :	non IGN
Thématique :	IMAGERIE
Nature :	Recueil / ouvrage collectif
DOI :	10.5772/intechopen.77202
date de publication en ligne :	03/10/2019
En ligne :	https://www.intechopen.com/books/satellite-information-classification-and-interp [...]
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95088

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Spatial Analysis, Modelling and Planning
Type de document :	Monographie
Auteurs :	Jorge Rocha, Editeur scientifique ; Jose Antonio Tenedório, Editeur scientifique
Editeur :	London [UK] : IntechOpen
Année de publication :	2018
ISBN/ISSN/EAN :	978-1-83881-795-4
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Analyse spatiale [Termes descripteurs IGN] analyse multicritère [Termes descripteurs IGN] cartographie des risques [Termes descripteurs IGN] changement d'occupation du sol [Termes descripteurs IGN] criminalité [Termes descripteurs IGN] croissance urbaine [Termes descripteurs IGN] données massives [Termes descripteurs IGN] géostatistique [Termes descripteurs IGN] maladie infectieuse [Termes descripteurs IGN] modélisation spatiale [Termes descripteurs IGN] planification [Termes descripteurs IGN] régression [Termes descripteurs IGN] réseau social [Termes descripteurs IGN] surveillance sanitaire [Termes descripteurs IGN] système d'information géographique
Résumé :	(auteur) New powerful technologies, such as geographic information systems (GIS), have been evolving and are quickly becoming part of a worldwide emergent digital infrastructure. Spatial analysis is becoming more important than ever because enormous volumes of spatial data are available from different sources, such as social media and mobile phones. When locational information is provided, spatial analysis researchers can use it to calculate statistical and mathematical relationships through time and space. This book aims to demonstrate how computer methods of spatial analysis and modeling, integrated in a GIS environment, can be used to better understand reality and give rise to more informed and, thus, improved planning. It provides a comprehensive discussion of spatial analysis, methods, and approaches related to planning.
Note de contenu :	1- Introductory Chapter: Spatial Analysis, Modelling, and Planning 2- One World, One Health Challenge: The Holistic Understanding of Rickettsiosis Integrating Multi-Criteria Analysis Techniques and Spatial Statistics 3- Spatial Analysis of Bifenthrin Sediment and Water Concentrations in California Waterbodies from 2001 to 2017 4- Absolute Density Measures Estimation Functions with Very High Resolution Satellite Images 5- Evaluating the Effectiveness of CCTV in Baltimore, Maryland 6- The Use of Photos of the Social Networks in Shaping a New Tourist Destination: Analysis of Clusters in a GIS Environment 7- Modelling Driving Forces of Urban Growth with Fuzzy Sets and GIS 8- Quantification and Prediction of Land Consumption and Its Climate Effects in the Rhineland Metropolitan Area Based on Multispectral Satellite Data and Land-Use Modelling 1975–2030 9- Fusion Study of Geography and Environmental Engineering 10- Generating Reality with Geosimulation Models: An Agent-Based Social-Spatial Network Modelling Perspective 11- Formal Urban Dynamics, Policy and Implications on Urban Planning: Perspectives on Kampala, Uganda 12- Risk Analysis and Land Use Planning 13- Political Economy and the Work of Kenneth Arrow
Numéro de notice :	25820
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE
Nature :	Monographie
En ligne :	https://www.intechopen.com/books/spatial-analysis-modelling-and-planning
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95089

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Advances in Intelligent Data Analysis XVIII : 18th International Symposium on Intelligent Data Analysis, IDA 2020, Konstanz, Germany, April 27–29 2020
Type de document :	Actes de congrès
Auteurs :	Michael R. Berthold, Editeur scientifique ; Ad Feelders, Editeur scientifique ; Georg Krempl, Editeur scientifique
Editeur :	Berlin, Heidelberg, Vienne, New York, ... : Springer
Année de publication :	2020
Collection :	Lecture notes in Computer Science, ISSN 0302-9743 num. 12080
Importance :	588 p.
ISBN/ISSN/EAN :	978-3-030-44584-3
Note générale :	Information Systems and Applications, incl. Internet/Web, and HCI
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Intelligence artificielle [Termes descripteurs IGN] analyse d'image numérique [Termes descripteurs IGN] analyse de données [Termes descripteurs IGN] apprentissage automatique [Termes descripteurs IGN] apprentissage dirigé [Termes descripteurs IGN] corrélation d'images [Termes descripteurs IGN] réseau neuronal artificiel [Termes descripteurs IGN] vision par ordinateur
Résumé :	(Editeur) This open access book constitutes the proceedings of the 18th International Conference on Intelligent Data Analysis, IDA 2020, held in Konstanz, Germany, in April 2020. The 45 full papers presented in this volume were carefully reviewed and selected from 114 submissions. Advancing Intelligent Data Analysis requires novel, potentially game-changing ideas. IDA’s mission is to promote ideas over performance: a solid motivation can be as convincing as exhaustive empirical evaluation.
Numéro de notice :	26312
Affiliation des auteurs :	non IGN
Thématique :	INFORMATIQUE
Nature :	Actes
DOI :	10.1007/978-3-030-44584-3
date de publication en ligne :	14/05/2020
En ligne :	https://www.springer.com/gp/book/9783030445836
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95127

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Mobile Mapping Technologies
Type de document :	Monographie
Auteurs :	Pablo Rodriguez-Gonzalvez, Editeur scientifique ; Erica Nocerino, Editeur scientifique ; Isabella Toschi, Editeur scientifique ; Kai-Wei Chiang, Editeur scientifique
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	334 p.
ISBN/ISSN/EAN :	978-3-03928-019-3
Note générale :	Bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Lasergrammétrie [Termes descripteurs IGN] carte d'intérieur [Termes descripteurs IGN] cartographie pour écran mobile [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] données localisées 3D [Termes descripteurs IGN] drone [Termes descripteurs IGN] positionnement en intérieur [Termes descripteurs IGN] semis de points [Termes descripteurs IGN] télémétrie laser terrestre
Résumé :	(Editeur) Mobile Mapping technologies have seen a rapid growth of research activity and interest in the last years, due to the increased demand of accurate, dense and geo-referenced 3D data. Their main characteristic is the ability of acquiring 3D information of large areas dynamically. This versatility has expanded their application fields from the civil engineering to a broader range (industry, emergency response, cultural heritage...), which is constantly widening. This increased number of needs, some of them specially challenging, is pushing the Scientific Community, as well as companies, towards the development of innovative solutions, ranging from new hardware / open source software approaches and integration with other devices, up to the adoption of artificial intelligence methods for the automatic extraction of salient features and quality assessment for performance verification The aim of the present book is to cover the most relevant topics and trends in Mobile Mapping Technology, and also to introduce the new tendencies of this new paradigm of geospatial science.
Numéro de notice :	26322
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE/IMAGERIE
Nature :	Recueil / ouvrage collectif
DOI :	10.3390/books978-3-03928-019-3
date de publication en ligne :	07/01/2020
En ligne :	https://doi.org/10.3390/books978-3-03928-019-3
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95150

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Remote sensing of above ground biomass
Type de document :	Monographie
Auteurs :	Lalit Kumar, Auteur ; Onisimo Mutanga, Auteur
Editeur :	Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI
Année de publication :	2019
Importance :	264 p.
ISBN/ISSN/EAN :	978-3-03921-210-1
Note générale :	Bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Applications de télédétection [Termes descripteurs IGN] biomasse aérienne [Termes descripteurs IGN] changement climatique [Termes descripteurs IGN] coefficient de corrélation [Termes descripteurs IGN] données lidar [Termes descripteurs IGN] image MODIS [Termes descripteurs IGN] Normalized Difference Vegetation Index [Termes descripteurs IGN] régression [Termes descripteurs IGN] série temporelle
Résumé :	(Editeur) Above ground biomass has been listed by the Intergovernmental Panel on Climate Change as one of the five most prominent, visible, and dynamic terrestrial carbon pools. The increased awareness of the impacts of climate change has seen a burgeoning need to consistently assess carbon stocks to combat carbon sequestration. An accurate estimation of carbon stocks and an understanding of the carbon sources and sinks can aid the improvement and accuracy of carbon flux models, an important pre-requisite of climate change impact projections. Based on 15 research topics, this book demonstrates the role of remote sensing in quantifying above ground biomass (forest, grass, woodlands) across varying spatial and temporal scales. The innovative application areas of the book include algorithm development and implementation, accuracy assessment, scaling issues (local–regional–global biomass mapping), and the integration of microwaves (i.e. LiDAR), along with optical sensors, forest biomass mapping, rangeland productivity and abundance (grass biomass, density, cover), bush encroachment biomass, and seasonal and long-term biomass monitoring.
Numéro de notice :	26325
Affiliation des auteurs :	non IGN
Thématique :	FORET/IMAGERIE
Nature :	Recueil / ouvrage collectif
DOI :	10.3390/books978-3-03921-210-1
date de publication en ligne :	09/12/2019
En ligne :	https://doi.org/10.3390/books978-3-03921-210-1
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95159

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Mobile Mapping : Space, Cartography and the Digital
Type de document :	Monographie
Auteurs :	Clancy Wilmott, Auteur
Editeur :	Amsterdam University Press
Année de publication :	2020
Importance :	349 p.
ISBN/ISSN/EAN :	978-90-485-3521-7
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Cartographie numérique [Termes descripteurs IGN] cartographie pour écran mobile [Termes descripteurs IGN] données localisées [Termes descripteurs IGN] épistémologie [Termes descripteurs IGN] histoire de la cartographie [Termes descripteurs IGN] lecture de carte [Termes descripteurs IGN] média [Termes descripteurs IGN] représentation cartographique [Termes descripteurs IGN] système de numérisation mobile
Résumé :	(éditeur) This book argues for a theory of mobile mapping, a situated and spatial approach towards researching how everyday digital mobile media practices are bound up in global systems of knowledge and power. Drawing from literature in media studies and geography - and the work of Michel Foucault and Doreen Massey - it examines how geographical and historical material, social, and cultural conditions are embedded in the way in which contemporary (digital) cartographies are read, deployed, and engaged. This is explored through seventeen walking interviews in Hong Kong and Sydney, as potent discourses like cartographic reason continue to transform and weave through the world in ways that haunt mobile mapping and bring old conflicts into new media. In doing so, Mobile Mapping offers an interdisciplinary rethinking about how multiple translations of spatial knowledges between rational digital epistemologies and tacit ways of understanding space and experience might be conceptualized and researched.
Note de contenu :	1- Maps, Mappers, Mapping 2- Sydney/Space 3- Cartography/Cities 4- Digital/Hong Kong 5- Mobile Mapping
Numéro de notice :	25832
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE
Nature :	Monographie
En ligne :	https://library.oapen.org/bitstream/handle/20.500.12657/37349/9789048535217.pdf? [...]
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95160

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contenu dans Directory of Open Access Books DOAB / Directory of Open Access Books DOAB

Titre :	Mapping society : The spatial dimensions of social cartography
Type de document :	Monographie
Auteurs :	Laura Vaughan, Auteur
Editeur :	Londres : University College London
Année de publication :	2018
Importance :	270 p.
ISBN/ISSN/EAN :	978-1-78735-305-3
Note générale :	bibliographie
Langues :	Anglais (eng)
Descripteur :	[Vedettes matières IGN] Cartographie [Termes descripteurs IGN] analyse visuelle [Termes descripteurs IGN] carte thématique [Termes descripteurs IGN] compréhension de l'image [Termes descripteurs IGN] géographie sociale [Termes descripteurs IGN] interprétation (psychologie) [Termes descripteurs IGN] population urbaine [Termes descripteurs IGN] sciences humaines et sociales [Termes descripteurs IGN] société [Termes descripteurs IGN] sociologie
Résumé :	(éditeur) From a rare map of yellow fever in eighteenth-century New York, to Charles Booth’s famous maps of poverty in nineteenth-century London, an Italian racial zoning map of early twentieth-century Asmara, to a map of wealth disparities in the banlieues of twenty-first-century Paris, Mapping Society traces the evolution of social cartography over the past two centuries. In this richly illustrated book, Laura Vaughan examines maps of ethnic or religious difference, poverty, and health inequalities, demonstrating how they not only serve as historical records of social enquiry, but also constitute inscriptions of social patterns that have been etched deeply on the surface of cities. The book covers themes such as the use of visual rhetoric to change public opinion, the evolution of sociology as an academic practice, changing attitudes to physical disorder, and the complexity of segregation as an urban phenomenon. While the focus is on historical maps, the narrative carries the discussion of the spatial dimensions of social cartography forward to the present day, showing how disciplines such as public health, crime science, and urban planning, chart spatial data in their current practice. Containing examples of space syntax analysis alongside full colour maps and photographs, this volume will appeal to all those interested in the long-term forces that shape how people live in cities.
Note de contenu :	1. Mapping the spatial logic of society 2. Disease, health and housing 3. Charles Booth and the mapping of poverty 4. Poverty mapping after Charles Booth 5. Nationalities, race and religion 6. Crime and disorder 7. Conclusions
Numéro de notice :	25798
Affiliation des auteurs :	non IGN
Thématique :	GEOMATIQUE
Nature :	Monographie
En ligne :	https://doabooks.org/doab?func=advancedSearch&uiLanguage=en&fromWeb=1&first=1&qu [...]
Format de la ressource électronique :	URL
Permalink :	https://documentation.ensg.eu/index.php?lvl=notice_display&id=95201

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Centre dedocumentationscientifique

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Centre dedocumentation
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