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Titre : Développement d’un "WebAppBuilder" pour applications cartographiques Type de document : Mémoire Auteurs : Fanny Vignolles, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 64 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse fonctionnelle (produit)
[Termes IGN] architecture d'applications web
[Termes IGN] méthode agile
[Termes IGN] portailIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) Magellium développe pour ses clients des portails web-cartographiques sur mesure. Cependant, de plus en plus d’utilisateurs recherchent une certaine forme d’autonomie dans la création et la personnalisation de leurs applications cartographiques. Ainsi pour mon stage, il m’a été demandé de développer un WebAppBuilder d’applications cartographiques. Ce portail web doit permettre, aux clients eux-mêmes, la personnalisation d’applications cartographiques par le biais de l’activation et du paramétrage de fonctionnalités et widgets usuels dans ce type d’applications, mais aussi l’administration en termes de droits de consultation et d’utilisateurs. Note de contenu :
Introduction
1. Contexte
1.1 Établissement d’accueil
1.2 Le projet de WebAppBuilder au sein du stage
1.3 Outils et ressources
2. Analyse
2.1 Analyse du besoin
2.2 Analyse fonctionnelle
2.3 Étude technique
3. Gestion de projet
3.1 Organisation et agilité
3.2 Outils de gestion de projet
3.3 Calendrier
4. Bilan
4.1 Réalisations
4.2 Difficultés rencontrées
4.3 Pistes d’amélioration
ConclusionNuméro de notice : 26189 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Magellium Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94160 Documents numériques
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Développement d’un "WebAppBuilder" pour applications cartographiques - pdf auteurAdobe Acrobat PDF Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons / Guillaume Lassalle (2019)
Titre : Exploitation of hyperspectral data for assessing vegetation health under exposure to petroleum hydrocarbons Type de document : Thèse/HDR Auteurs : Guillaume Lassalle, Auteur ; Arnaud Elger, Directeur de thèse ; Sophie Fabre, Directeur de thèse Editeur : Toulouse : Université Fédérale Toulouse Midi-Pyrénées Année de publication : 2019 Autre Editeur : Toulouse : Institut Supérieur de l’Aéronautique et de l’Espace Importance : 277 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse en vue de l'obtention du Doctorat de l'Université de Toulouse délivré par l'Institut Supérieur de l’Aéronautique et de l’Espace, spécialité : Surfaces et interfaces continentales, Hydrologie Agrosystèmes, écosystèmes et environnementLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] canopée
[Termes IGN] contamination
[Termes IGN] feuille (végétation)
[Termes IGN] hydrocarbure
[Termes IGN] image aérienne
[Termes IGN] image hyperspectrale
[Termes IGN] indice de végétation
[Termes IGN] modèle de transfert radiatif
[Termes IGN] pollution des sols
[Termes IGN] prospection pétrolière
[Termes IGN] réflectance spectrale
[Termes IGN] régression multiple
[Termes IGN] signature spectrale
[Termes IGN] surveillance de la végétationIndex. décimale : THESE Thèses et HDR Résumé : (auteur) Oil exploration and contamination monitoring remain limited in regions covered by vegetation. Natural seepages and oil leakages due to facility failures are often masked by the foliage, making ineffective the current technologies used for detecting crude oil and petroleum products. However, the exposure of vegetation to oil affects its health and, consequently, its optical properties in the [400:2500] nm domain. This suggest being able to detect seepages and leakages indirectly, by analyzing vegetation health through its spectral reflectance. Based on this assumption, this thesis evaluates the potential of airborne hyperspectral imagery with high spatial resolution for detecting and quantifying oil contamination in vegetated regions. To achieve this, a three-step multiscale approach was adopted. The first step aimed at developing a method for detecting and characterizing the contamination under controlled conditions, by exploiting the optical properties of Rubus fruticosus L. The proposed method combines 14 vegetation indices in classification and allows detecting various oil contaminants accurately, from leaf to canopy scale. Its use under natural conditions was validated on a contaminated mud pit colonized by the same species. During the second step, a method for quantifying total petroleum hydrocarbons, based on inverting the PROSPECT model, was developed. The method exploits the pigment content of leaves, estimated from their spectral signature, for predicting the level of hydrocarbon contamination in soils accurately. The last step of the approach demonstrated the robustness of the two methods using airborne imagery. They proved performing for detecting and quantifying mud pit contamination. Another method of quantification, based on multiple regression, was proposed. At the end of this thesis, the three methods proposed were validated for use both on the field, at leaf and canopy scales, and on airborne hyperspectral images with high spatial resolution. Their performances depend however on the species, the season and the level of soil contamination. A similar approach was conducted under tropical conditions, allowing the development of a method for quantifying the contamination adapted to this context. In a perspective of operational use, an important effort is still required for extending the scope of the methods to other contexts and for anticipating their use on satellite- and drone-embedded hyperspectral sensors. Finally, the contribution of active remote sensing (radar and LiDAR) should be considered in further research, in order to overcome some of the limits specific to passive optical remote sensing. Note de contenu : General introduction
1- State-of-the-art of passive hyperspectral remote sensing for oil exploration and contamination monitoring in vegetated regions
2- Development of methods for detecting and quantifying oil contamination based on vegetation optical properties, under controlled conditions
3- Application and evaluation of the methods under natural conditions, from field scale to airborne hyperspectral imagery
General conclusionNuméro de notice : 25946 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Thèse française Note de thèse : Thèse de Doctorat : Spécialité : Surfaces et interfaces continentales, Hydrologie Agrosystèmes, écosystèmes et environnement : Toulouse : 2019 nature-HAL : Thèse DOI : sans En ligne : http://www.theses.fr/2019ESAE0030 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96343
Titre : Google Earth Engine applications Type de document : Monographie Auteurs : Lalit Kumar, Éditeur scientifique ; Onisimo Mutanga, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 420 p. Format : 17 x 25 cm ISBN/ISSN/EAN : 978-3-03897-885-5 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Information géographique
[Termes IGN] base de données d'images
[Termes IGN] Google Earth Engine
[Termes IGN] image 3D
[Termes IGN] image aérienne
[Termes IGN] image satellite
[Termes IGN] information géographique numérique
[Termes IGN] informatique en nuage
[Termes IGN] moteur de recherche
[Termes IGN] surveillance écologique
[Termes IGN] système d'information environnementale
[Termes IGN] traitement de données localiséesRésumé : (éditeur) In a rapidly changing world, there is an ever-increasing need to monitor the Earth's resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth's surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales. Note de contenu : 1- Google Earth Engine applications since inception: usage, trends, and potential
2- Global estimation of biophysical variables from Google Earth Engine platform
3- An operational before-after-control-impact (BACI) designed platform for vegetation monitoring at planetary scale
4- Mapping vegetation and land use types in Fanjingshan national nature reserve using Google Earth Engine
5- A dynamic Landsat derived Normalized Difference Vegetation Index (NDVI) product for the conterminous United States
6- High spatial resolution visual band imagery outperforms medium resolution spectral imagery for ecosystem assessment in the semi-arid Brazilian Sert˜ao
7- Assessing the spatial and occupation dynamics of the Brazilian pasturelands based on the automated classification of MODIS images from 2000 to 2016
8- Towards global-scale seagrass mapping and monitoring using Sentinel-2 on Google Earth Engine: The case study of the Aegean and Ionian Seas
9- BULC-U: Sharpening resolution and improving accuracy of land-use/land-cover classifications in Google Earth Engine
10- Monitoring the impact of land cover change on surface urban heat island through Google
Earth Engine: Proposal of a global methodology, first applications and problems
11- Regional crop gross primary productivity and yield estimation using fused Landsat-MODIS data
12- The first wetland inventory map of Newfoundland at a spatial resolution of 10 m using Sentinel-1 and Sentinel-2 data on the Google Earth Engine cloud computing platform
13- A cloud-based multi-temporal ensemble classifier to map smallholder farming systems
14- Nominal 30-m cropland extent map of continental Africa by integrating pixel-based and object-based algorithms using Sentinel-2 and Landsat-8 data on Google Earth Engine
15- SnowCloudHydro — A new framework for forecasting streamflow in snowy, data-scarce regions
16- Flood prevention and emergency response system powered by Google Earth Engine
17- Leveraging the Google Earth Engine for drought assessment using global soil moisture data
18- Multitemporal cloud masking in the Google Earth Engine
19- Historical and operational monitoring of surface sediments in the lower Mekong basin using Landsat and Google Earth Engine cloud computing
20- Mapping mining areas in the Brazilian Amazon using MSI/Sentinel-2 imagery (2017)
21- Estimating satellite-derived bathymetry (SDB) with the Google Earth Engine and Sentinel-2
22- Mean composite fire severity metrics computed with Google Earth Engine offer improved accuracy and expanded mapping potentialNuméro de notice : 25887 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Monographie DOI : 10.3390/books978-3-03897-885-5 En ligne : https://doi.org/10.3390/books978-3-03897-885-5 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95788
Titre : Learning scene geometry for visual localization in challenging conditions Type de document : Article/Communication Auteurs : Nathan Piasco , Auteur ; Désiré Sidibé, Auteur ; Valérie Gouet-Brunet , Auteur ; Cédric Demonceaux, Auteur Editeur : New York : Institute of Electrical and Electronics Engineers IEEE Année de publication : 2019 Projets : PLaTINUM / Gouet-Brunet, Valérie Conférence : ICRA 2019, International Conference on Robotics and Automation 20/05/2019 24/05/2019 Montréal Québec - Canada Proceedings IEEE Importance : pp 9094 - 9100 Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse d'image orientée objet
[Termes IGN] analyse visuelle
[Termes IGN] appariement d'images
[Termes IGN] carte de profondeur
[Termes IGN] descripteur
[Termes IGN] géométrie de l'image
[Termes IGN] image RVB
[Termes IGN] localisation basée vision
[Termes IGN] précision de localisation
[Termes IGN] prise de vue nocturne
[Termes IGN] robotique
[Termes IGN] scène urbaine
[Termes IGN] variation diurne
[Termes IGN] variation saisonnière
[Termes IGN] vision par ordinateurRésumé : (auteur) We propose a new approach for outdoor large scale image based localization that can deal with challenging scenarios like cross-season, cross-weather, day/night and longterm localization. The key component of our method is a new learned global image descriptor, that can effectively benefit from scene geometry information during training. At test time, our system is capable of inferring the depth map related to the query image and use it to increase localization accuracy. We are able to increase recall@1 performances by 2.15% on cross-weather and long-term localization scenario and by 4.24% points on a challenging winter/summer localization sequence versus state-of-the-art methods. Our method can also use weakly annotated data to localize night images across a reference dataset of daytime images. Numéro de notice : C2019-002 Affiliation des auteurs : LASTIG MATIS+Ext (2012-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1109/ICRA.2019.8794221 Date de publication en ligne : 12/08/2019 En ligne : http://doi.org/10.1109/ICRA.2019.8794221 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93774 Documents numériques
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Learning scene geometry... - pdf auteurAdobe Acrobat PDF
Titre : Multifunctional land uses in Africa : Sustainable food security solutions Type de document : Monographie Auteurs : Elisabeth Simelton, Éditeur scientifique ; Madelene Ostwald, Éditeur scientifique Editeur : Londres : Routledge Année de publication : 2019 Importance : 176 p. ISBN/ISSN/EAN : 978-0-367-24644-0 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Agriculture
[Termes IGN] Afrique (géographie politique)
[Termes IGN] agroforesterie
[Termes IGN] alimentation
[Termes IGN] aquaculture
[Termes IGN] changement climatique
[Termes IGN] changement d'utilisation du sol
[Termes IGN] développement durable
[Termes IGN] gestion de l'eau
[Termes IGN] ressources naturelles
[Termes IGN] sécurité alimentaire
[Termes IGN] surface cultivéeRésumé : (éditeur) This book presents contemporary case studies of land use, management practices, and innovation in Africa with a view to exploring how multifunctional land uses can alleviate food insecurity and poverty. Food security and livelihoods in Africa face multiple challenges in the form of feeding a growing population on declining land areas under the impacts of climate change. The overall question is what kind of farming systems can provide resilient livelihoods? This volume presents a selection of existing farming systems that demonstrate how more efficient use of land and natural resources, labour and other inputs can have positive effects on household food security and livelihoods. It examines how aquaculture, integrated water management, peri-urban farming systems, climate-smart agriculture practices and parkland agroforestry contribute multiple benefits. Drawing on case studies from Kenya, Ethiopia, Nigeria and Burkina Faso, contributed by young African scientists, this book provides a unique perspective on multifunctional land use in Africa and illustrates how non-conventional uses can be profitable while promoting social and environmental sustainability. Tapping into the global discussion on land scarcity and linking food security to existing land use change processes, this volume will stimulate readers looking for diversified land uses that are compatible with both household and national food security ambitions. This book will be of great interest to students and scholars of African development, agriculture, food security, land use and environmental management, as well as sustainable development more generally, in addition to policymakers and practitioners working in these areas. Note de contenu : 1- Multifunctional land-use systems – a solution for food security in Africa?
2- Nigerian climate-smart agriculture practices with scaling potential
3- Treating shea trees as crops improves women’s livelihoods in Burkina Faso
4- Economic benefits from cassava in peri-urban multiple-cropping systems in Nigeria
5- Integrated aquaculture
6- What integrated watershed management can deliver for the environment and livelihoods
7- Smallholder maize-based systems
8- Multifunctional land-use practices in AfricaNuméro de notice : 25850 Affiliation des auteurs : non IGN Nature : Monographie DOI : sans En ligne : https://www.taylorfrancis.com/books/e/9780429283666 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95440 Numérique et territoires / Philippe Cohard (2019)PermalinkPermalinkSUMAC 2019, 1st workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2019)PermalinkPermalinkWebscraping, bigdata et analyse spatiale de données immobilières : réponse à un projet ESPON au sein de l'UMS RIATE / Marc Lieury (2019)PermalinkPerformance analysis of PPP positioning method by using IGS real-time service / Tatjana Kuzmić in Geodetski vestnik, vol 62 n° 4 (December 2018 - February 2019)PermalinkApplication of Landsat-8 and ASTER satellite remote sensing data for porphyry copper exploration: a case study from Shahr-e-Babak, Kerman, south of Iran / Morteza Safari in Geocarto international, vol 33 n° 11 (November 2018)PermalinkSpecies mixing effects on forest productivity : A case study at stand-, species- and tree-level in the Netherlands / Huicui Lu in Forests, vol 9 n° 11 (November 2018)PermalinkToward a participatory VGI methodology : crowdsourcing information on regional food assets / Victoria Fast in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)PermalinkDetecting the competition between Moso bamboos and broad-leaved trees in mixed forests using a terrestrial laser scanner / Yingjie Yan in Forests, vol 9 n° 9 (September 2018)Permalink