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Titre : Innovative geo-information tools for governance Type de document : Monographie Auteurs : Yola Georgiadou, Éditeur scientifique ; Diana Reckien, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 186 p. Format : 16 x 24 cm ISBN/ISSN/EAN : 978-3-03921-338-2 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] chaleur
[Termes IGN] changement climatique
[Termes IGN] énergie renouvelable
[Termes IGN] gestion de l'eau
[Termes IGN] information géographique
[Termes IGN] outil d'aide à la décision
[Termes IGN] politique publique
[Termes IGN] recherche interdisciplinaire
[Termes IGN] surveillance hydrologique
[Termes IGN] téléphone intelligent
[Termes IGN] urbanisationRésumé : (éditeur) In current times, highly complex and urgent policy problems--e.g., climate change, rapid urbanization, equitable access to key services, land rights, and massive human resettlement--challenge citizens, NGOs, private corporations, and governments at all levels. These policy problems, often called 'wicked', involve multiple causal factors, anticipated and unanticipated effects, as well as high levels of disagreement among stakeholders about the nature of the problem and the appropriateness of solutions. Given the wickedness of such policy problems, interdisciplinary and longitudinal research is required, integrating and harnessing the diverse skills and knowledge of urban planners, anthropologists, geographers, geo-information scientists, economists, and others. This Special Issue promotes innovative concepts, methods, and tools, as well as the role of geo-information, to help (1) analyze alternative policy solutions, (2) facilitate stakeholder dialogue, and (3) explore possibilities for tackling wicked problems related to climate change, rapid urbanization, equitable access to key services (such as water and health), land rights, and human resettlements in high-, middle-, and low-income countries in the North and South. Such integrative approaches can deepen our understanding of how different levels of government and governance reach consensus, despite diverging beliefs and preferences. Due to the particularly complex spatiotemporal characteristics of wicked policy problems, innovative concepts, alternative methods, and new geo-information tools play a significant role. Note de contenu : 1- Monitoring Rural Water Points in Tanzania with Mobile Phones: The Evolution of the
SEMA App
2- An Interactive Planning Support Tool for Addressing Social Acceptance of Renewable Energy Projects in The Netherlands
3- The Governance Landscape of Geospatial E-Services—The Belgian Case
4- Closing Data Gaps with Citizen Science?Findings from the Danube Region
5- Tensions in Rural Water Governance: The Elusive Functioning of Rural Water Points in Tanzania
6- Evolving Spatial Data Infrastructures and the Role of Adaptive Governance
7- Wicked Water Points: The Quest for an Error Free National Water Point Database
8- What do New Yorkers Think about Impacts and Adaptation to Heat Waves? An Evaluation
Tool to Incorporate Perception of Low-Income Groups into Heat Wave Adaptation Scenarios in New York City
9-Numéro de notice : 25988 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/URBANISME Nature : Monographie DOI : 10.3390/books978-3-03921-338-2 En ligne : https://doi.org/10.3390/books978-3-03921-338-2 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96754 Investigating the accuracy of a bathymetric refraction correction on Structure from Motion photogrammetric datasets / Aelaïg Cournez (2019)
Titre : Investigating the accuracy of a bathymetric refraction correction on Structure from Motion photogrammetric datasets : River Feshie, Scotland Type de document : Mémoire Auteurs : Aelaïg Cournez, Auteur Editeur : Champs-sur-Marne : Ecole nationale des sciences géographiques ENSG Année de publication : 2019 Importance : 79 p. Format : 21 x 30 cm Note générale : Bibliographie
Rapport de projet pluridisciplinaire, cycle ING2Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications photogrammétriques
[Termes IGN] acquisition de données
[Termes IGN] correction automatique
[Termes IGN] correction des altitudes
[Termes IGN] données bathymétriques
[Termes IGN] drone
[Termes IGN] Ecosse
[Termes IGN] géomorphologie locale
[Termes IGN] réfraction de l'eau
[Termes IGN] rivière
[Termes IGN] semis de pointsIndex. décimale : PROJET Mémoires : Rapports de projet - stage des ingénieurs de 2e année Résumé : (Auteur) L’étude géomorphologique des rivières est essentielle dans la préservation des milieux naturels et de la biodiversité fluviale. Dans ce contexte, de nombreuses technologies sont développées afin de surveiller ces espaces aux cours des années et d’étudier leurs dynamiques hydrauliques et sédimentaires. L’essor des innovations en photogrammétrie permettent aujourd’hui de modéliser aisément un environnement à l’échelle d’une rivière sous forme d’un nuage de points 3D géo-référencés à partir d’acquisitions par drone. Or les données bathymétriques issues de ces acquisitions restent entachées d’une forte erreur en élévation due au phénomène de réfraction optique ayant lieu à l’interface entre l’air et l’eau. Ces dernières années, plusieurs algorithmes permettant de corriger cette erreur virent le jour tel que celui proposé par J.T. Dietrich. Or, à ce jour, cet algorithme ne fut testé que sur des portions de rivières limitées (200 mètres). Le but de ce projet de stage fut donc d’évaluer les performances de cet algorithme en termes de correction de l’élévation sur une portion d’environ deux kilomètres de rivière à chenaux en tresse et d’évaluer notamment les erreurs dues à la végétation et aux bassins profonds. Note de contenu : Introduction
1. Methods: Fieldwork
1.1 Study area
1.2 2019 surveys
1.3 Resulting datasets
1.4 Historic survey data
2. Methods: Processing
2.1 Topographic modelling
2.2 Water surface modelling
2.3 Pre-process steps before Dietrich algorithm execution
2.4 Description of Dietrich algorithm
3. Results
3.1 Elevation correction
3.2 Elevation errors and depth
3.3 Elevation errors associated with vegetation and complex bank heights
3.4 Elevation errors and geomorphic units
ConclusionNuméro de notice : 26122 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Mémoire de projet pluridisciplinaire Organisme de stage : Geographical and Earth Sciences School (University of Glasgow) Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93863 Documents numériques
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Investigating the accuracy of a bathymetric refraction correction... - pdf auteurAdobe Acrobat PDF Machine learning and geographic information systems for large-scale mapping of renewable energy potential / Dan Assouline (2019)
Titre : Machine learning and geographic information systems for large-scale mapping of renewable energy potential Type de document : Thèse/HDR Auteurs : Dan Assouline, Auteur ; Jean-Louis Scartezzini, Directeur de thèse ; Nahid Mohajeri Pour Rayeni, Directeur de thèse Editeur : Lausanne : Ecole Polytechnique Fédérale de Lausanne EPFL Année de publication : 2019 Importance : 294 p. Format : 21 x 30 cm Note générale : bibliographie
Thèse présentée pour l'obtention du grade de Docteur ès Sciences à l'Ecole Polytechnique Fédérale de LausanneLangues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] apprentissage automatique
[Termes IGN] carte thématique
[Termes IGN] classification dirigée
[Termes IGN] classification par forêts d'arbres décisionnels
[Termes IGN] classification par séparateurs à vaste marge
[Termes IGN] données météorologiques
[Termes IGN] données topographiques
[Termes IGN] énergie éolienne
[Termes IGN] énergie géothermique
[Termes IGN] énergie renouvelable
[Termes IGN] énergie solaire
[Termes IGN] méthode fondée sur le noyau
[Termes IGN] modélisation spatio-temporelle
[Termes IGN] occupation du sol
[Termes IGN] prédiction
[Termes IGN] SuisseIndex. décimale : THESE Thèses et HDR Résumé : (auteur) A promising pathway to follow in order to reach sustainable development goals is an increased
reliance on renewable sources of energy. The optimized use of these energy sources, however, requires the assessment of their potential supply, along with the demand loads in locations of interest. In particular, large-scale supply estimation studies are needed in order to evaluate areas of high potential for each type of energy source for a particular region, and allow for the elaboration of efficient global energy strategies. In Switzerland, the “Energy Strategy 2050”, initiated in 2011 by the Swiss Federal Council, sets an example with the ambitious goal of reaching a 50-80% reduction of CO2 emissions by the year 2050, with a clear course of action: phasing-out nuclear power, improving energy efficiency, and greatly increasing the use of renewables. This thesis develops a general data-driven strategy combining Geographic Information Systems and Machine Learning methods to map the large-scale energy potential for three very popular sources of decentralized energy systems: wind energy (using horizontal axis wind turbines), geothermal energy (using very shallow ground source heat pumps) and solar energy (using photovoltaic solar panels over rooftops). For each of the three considered energy sources, an adapted methodology is suggested to assess its large-scale potential, by estimating multiple variables of interest (with a suitable time resolution, e.g. monthly or yearly), using widely available data, and combining these variables into potential values. These latter estimated variables, dictating the potential, include: (i) the monthly wind speed, and rural and urban topographic/obstacle configuration for wind energy, (ii) the ground thermal conductivity, volumetric heat capacity and monthly temperature gradient for geothermal energy, (iii) the monthly solar radiation, available area for PV panels over rooftops, geometrical characteristics of rooftops and monthly shading factors over rooftops for solar energy. The use of Machine Learning algorithms (notably Support Vector Machines and Random Forests) allows, given adequate features and training data (examples for some locations), for the prediction of the latter variables at unknown locations, along with the uncertainty attached to the predictions. In each case, the developed methodology is set-up with an aim to be applied for Switzerland, meaning that it relies on Swiss available energy-related data. Such data, however, including meteorological, topographic, ground/soil-related and building-related data, is becoming progressively available for most countries, making it possible to widely generalize the proposed methodologies.
Results show that Machine Learning is adequate for energy potential estimation, as the multiple required predictions and spatial extrapolations are achieved with reasonable accuracy. In addition, final values are validated with other existing data or studies when possible, and show general agreement. The application of the suggested potential methodologies in Switzerland outline the very significant potential for the considered renewables. In particular, there is a relatively high potential for RooftopMounted solar PV panels, as it is estimated that they could generate a total electricity production of 16.3 TWh per year, which corresponds to 25.3% of the annual electricity demand in 2017.In each case, the developed methodology is set-up with an aim to be applied for Switzerland, meaning that it relies on Swiss available energy-related data. Such data, however, including meteorological, topographic, ground/soil-related and building-related data, is becoming progressively available for most countries, making it possible to widely generalize the proposed methodologies. Results show that Machine Learning is adequate for energy potential estimation, as the multiple required predictions and spatial extrapolations are achieved with reasonable accuracy. In addition, final values are validated with other existing data or studies when possible, and show general agreement. The application of the suggested potential methodologies in Switzerland outline the very significant potential for the considered renewables. In particular, there is a relatively high potential for RooftopMounted solar PV panels, as it is estimated that they could generate a total electricity production of 16.3 TWh per year, which corresponds to 25.3% of the annual electricity demand in 2017.Note de contenu : 1- Introduction
2- Machine Learning
3- Theory and modeling of renewable energy systems
4- Wind energy: a theoretical potential estimation
5- Very shallow geothermal energy: a theoretical potential estimation
6- Solar energy: a technical potential estimation at commune scale
7- Solar energy: an improved potential estimation at pixel scale
8- ConclusionNuméro de notice : 25797 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse française Note de thèse : Thèse de Doctorat : Sciences : EPFLausanne : 2019 nature-HAL : Thèse DOI : sans En ligne : https://infoscience.epfl.ch/record/264971?ln=fr Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95038 Macroalgues intertidales : Apport de la télédétection hyperspectrale pour le suivi sectoriel dans le cadre de la DCE/DCSMM / Arnaud Le Bris (2019)
Titre : Macroalgues intertidales : Apport de la télédétection hyperspectrale pour le suivi sectoriel dans le cadre de la DCE/DCSMM Type de document : Article/Communication Auteurs : Arnaud Le Bris , Auteur ; T. Perrot, Auteur ; P.O. Liabot, Auteur ; C. Daniel, Auteur ; S. Richier, Auteur Editeur : Saint-Mandé : Institut national de l'information géographique et forestière - IGN (2012-) Année de publication : 2019 Conférence : SFPT 2019, 7ème colloque scientifique du Groupe Hyperspectral 09/07/2019 10/07/2019 Toulouse France programme sans actes Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] algue
[Termes IGN] image hyperspectrale
[Termes IGN] marée océaniqueNuméro de notice : C2019-060 Affiliation des auteurs : LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Communication nature-HAL : ComSansActesPubliés-Unpublished DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96915 Microwave indices from active and passive sensors for remote sensing applications / Emanuele Santi (2019)
Titre : Microwave indices from active and passive sensors for remote sensing applications Type de document : Monographie Auteurs : Emanuele Santi, Éditeur scientifique ; Simonetta Paloscia, Éditeur scientifique Editeur : Bâle [Suisse] : Multidisciplinary Digital Publishing Institute MDPI Année de publication : 2019 Importance : 224 p. Format : 18 x 26 cm ISBN/ISSN/EAN : 978-3-03897-820-6 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications de télédétection
[Termes IGN] bande C
[Termes IGN] bande Ku
[Termes IGN] bande X
[Termes IGN] diffusométrie
[Termes IGN] filtrage spatiotemporel
[Termes IGN] glace de mer
[Termes IGN] humidité du sol
[Termes IGN] image radar moirée
[Termes IGN] phénologie
[Termes IGN] prairie
[Termes IGN] série temporelleRésumé : (éditeur) Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices. Note de contenu : Editorial
1- Ku-, X- and C-Band microwave backscatter indices from saline snow covers on Arctic first-year sea ice
2- Retrieval of effective correlation length and snow water equivalent from radar and passive microwave measurements
3- Soil moisture from fusion of scatterometer and SAR: closing the scale gap with temporal filtering
4- Using SAR-derived vegetation descriptors in a water cloud model to improve soil
moisture retrieval
5- Sensitivity of Sentinel-1 backscatter to vegetation dynamics: An Austrian case study
6- AMSR2 soil moisture downscaling using temperature and vegetation data
7- Analysis of the Radar Vegetation Index and potential improvements
8- Radiometric microwave indices for remote sensing of land surfaces
9- Soil moisture in the Biebrza wetlands retrieved from Sentinel-1 imagery
10- Exploiting time series of Sentinel-1 and Sentinel-2 imagery to detect meadow phenology in mountain regionsNuméro de notice : 25941 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Monographie DOI : 10.3390/books978-3-03897-821-3 En ligne : https://doi.org/10.3390/books978-3-03897-821-3 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96313 Monitoring crops water needs at high spatio-temporal resolution by synergy of optical / thermal and radar observations / Abdelhakim Amazirh (2019)PermalinkPermalinkPermalinkPermalinkObjets et relations spatiales composites et prise en compte du vague pour interpréter un référencement spatial indirect / Mattia Bunel in Revue internationale de géomatique, vol 29 n° 1 (janvier - mars 2019)PermalinkQuality assessment of CNES real-time ionospheric products / Zhixi Nie in GPS solutions, vol 23 n° 1 (January 2019)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkPermalinkRéorganisation du SIG et valorisation des données du Parc Naturel Régional du Gâtinais français / Paul Roux (2019)PermalinkRetrieving relevant land cover and land use data to study urban climate change / Bénédicte Bucher (2019)PermalinkPermalinkPermalinkPermalinkSimultaneous characterization of objects temperature and radiative properties through multispectral infrared thermography / Thibaud Toullier (2019)PermalinkPermalinkPermalinkTempête Xynthia à la Faute-sur-Mer : une analyse a posteriori de l’impact des « zones noires » et des alternatives possibles / Axel Creach in Norois, n° 251 ([01/01/2019])PermalinkToward global soil moisture monitoring with sentinel-1 : harnessing assets and overcoming obstacles / Bernhard Bauer-Marschallinger in IEEE Transactions on geoscience and remote sensing, vol 57 n° 1 (January 2019)PermalinkUnderstanding of atmospheric systems with efficient numerical methods for observation and prediction / Lei-Ming Ma (2019)PermalinkVariabilité du niveau marin relatif le long du littoral de Brest (France) par combinaison de méthodes géodésiques spatiales (altimétrie radar, InSAR et GPS) / Cyril Poitevin (2019)Permalink4-dimensional recording and visualization of urban archeological excavations / Gabriele Bitelli in Applied geomatics, vol 10 n° 4 (December 2018)PermalinkAtmospheric artifacts correction with a covariance-weighted linear model over mountainous regions / Zhongbo Hu in IEEE Transactions on geoscience and remote sensing, vol 56 n° 12 (December 2018)PermalinkEnhanced local ionosphere model for multi-constellations single frequency precise point positioning applications: Egyptian case study / Emad El Manaily in Artificial satellites, vol 53 n° 4 (December 2018)PermalinkGIS approach to publishing commonfacilities plans of land consolidation in the Czech Republic / Arnošt Müller in Geodetski vestnik, vol 62 n° 4 (December 2018 - 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