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Patrimoine arboré : pousser de nouvelles pratiques / Xavier Fodor in SIGmag, n° 22 (octobre 2019)
[article]
Titre : Patrimoine arboré : pousser de nouvelles pratiques Type de document : Article/Communication Auteurs : Xavier Fodor, Auteur Année de publication : 2019 Article en page(s) : pp 39 - 39 Langues : Français (fre) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] Genève
[Termes IGN] gestion forestière
[Termes IGN] inventaire forestier local
[Termes IGN] patrimoine naturel
[Termes IGN] système d'information forestierRésumé : (Auteur) Inventorier à l'échelle d'un canton un patrimoine arboré ensuite géré dans chaque commune nécessite d'adopter un langage commun. Les habitudes de travail doivent aussi évoluer. Numéro de notice : A2019-422 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article nature-HAL : ArtSansCL DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93705
in SIGmag > n° 22 (octobre 2019) . - pp 39 - 39[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 147-2019031 RAB Revue Centre de documentation En réserve L003 Disponible High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland / Karina Wilgan in Journal of geodesy, vol 93 n°6 (June 2019)
[article]
Titre : High-resolution models of tropospheric delays and refractivity based on GNSS and numerical weather prediction data for alpine regions in Switzerland Type de document : Article/Communication Auteurs : Karina Wilgan, Auteur ; Alain Geiger, Auteur Année de publication : 2019 Article en page(s) : pp 819 - 835 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications de géodésie spatiale
[Termes IGN] Alpes
[Termes IGN] collocation par moindres carrés
[Termes IGN] correction troposphérique
[Termes IGN] données GNSS
[Termes IGN] données météorologiques
[Termes IGN] interféromètrie par radar à antenne synthétique
[Termes IGN] modèle mathématique
[Termes IGN] précision de l'estimation
[Termes IGN] prévision météorologique
[Termes IGN] réfraction
[Termes IGN] retard troposphérique
[Termes IGN] retard troposphérique zénithal
[Termes IGN] SuisseRésumé : (auteur) The tropospheric delay of a microwave signal affects all space geodetic techniques. One possibility of modeling the delay is by introducing tropospheric models from external data sources. In this study, we present high-resolution models of tropospheric total refractivity and zenith total delay (ZTD) for the alpine area in Switzerland. The troposphere models are based on different combinations of data sources, including numerical weather prediction (NWP) model COSMO-1 with high spatial resolution of 1.1 km × 1.1 km, GNSS data from permanent geodetic stations and GPS L1-only data from low-cost permanent stations. The tropospheric parameters are interpolated to the arbitrary locations by the least-squares collocation method using the in-house developed software package COMEDIE (Collocation of Meteorological Data for Interpretation and Estimation of Tropospheric Pathdelays). The first goal of this study is to validate the obtained models with the reference radiosonde and GNSS data to show the improvement w.r.t. the previous studies that used lower resolution input data. In case of total refractivity, the profiles reconstructed from COSMO-1 model show the best agreement with the reference radiosonde measurements, with an average bias of 1.1 ppm (0.6% of the total refractivity value along a vertical profile) and standard deviation of 2.6 ppm (1.6%) averaged from the whole profile. The radiosondes are assimilated into COSMO-1 model; thus, a high correlation is expected, and this comparison is not independent. In case of ZTD, the GNSS-based model shows the highest agreement with the reference GNSS data, with an average bias of 0.2 mm (0.01%) and standard deviation of 4.3 mm (0.2%). For COSMO-based model, the agreement is also very high, especially compared to our previous studies with lower resolution NWPs. The average bias is equal to − 2.5 mm (0.1%) with standard deviation of 9.2 mm (0.5%). The second goal of this study is to test the feasibility of calculating high-resolution troposphere models over a limited area from coarser data sets. We calculate the ZTD models with spatial resolution of 20 m for a test area in Matter Valley. We include the information from the low-cost GPS stations (X-Sense), to also assess the performance and future usability of such stations. We validate the models based on three data sources w.r.t. the reference GNSS data. For the station located inside the area of the study, the models have an agreement of few mm with the reference data. For stations located further away from the study area, the agreement for X-Sense is smaller, but the standard deviations of residuals are still below 15 mm. We consider also another factor of evaluating the high-resolution models, i.e., spatial variability of the data. For designing a GNSS network, also for the tropospheric estimates, the height variability of the network may be as important as the horizontal distribution. The GNSS-based models are built from the coarsest network; thus, their variability is the lowest. The variability of X-Sense-based stations is the highest; thus, such data may be suitable for building troposphere models for very high-resolution applications. Numéro de notice : A2019-350 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-018-1203-6 Date de publication en ligne : 01/10/2018 En ligne : https://doi.org/10.1007/s00190-018-1203-6 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=93394
in Journal of geodesy > vol 93 n°6 (June 2019) . - pp 819 - 835[article]Comparaison de MNT à haute résolution issus de techniques laser et photogrammétriques / Michel Kasser in XYZ, n° 158 (mars 2019)
[article]
Titre : Comparaison de MNT à haute résolution issus de techniques laser et photogrammétriques Type de document : Article/Communication Auteurs : Michel Kasser , Auteur ; Nicolas Delley, Auteur ; Stéphane Cretegny, Auteur Année de publication : 2019 Article en page(s) : pp 17 - 20 Note générale : bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Acquisition d'image(s) et de donnée(s)
[Termes IGN] analyse comparative
[Termes IGN] image à haute résolution
[Termes IGN] image captée par drone
[Termes IGN] modèle numérique de terrain
[Termes IGN] montagne
[Termes IGN] photogrammétrie aérienne
[Termes IGN] télémétrie laser aéroporté
[Termes IGN] Vaud (Suisse)Résumé : (auteur) Dans le cadre d'une étude génomique de plantes de haute altitude nécessitant des modèles de terrain extrêmement précis, une étude sur les comparaisons de modèles acquis par des outils différents a été menée, ceci dans des sites sans végétation haute. Diverses pistes sont présentées pour expliquer les différences observées. Numéro de notice : A2019-082 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=92219
in XYZ > n° 158 (mars 2019) . - pp 17 - 20[article]Exemplaires(1)
Code-barres Cote Support Localisation Section Disponibilité 112-2019011 RAB Revue Centre de documentation En réserve L003 Disponible How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession? / Marco Vanoni in Forest ecology and management, vol 433 (15 February 2019)
[article]
Titre : How do tree mortality models from combined tree-ring and inventory data affect projections of forest succession? Type de document : Article/Communication Auteurs : Marco Vanoni, Auteur ; Maxime Cailleret, Auteur ; Lisa Hülsmann, Auteur ; et al., Auteur Année de publication : 2019 Article en page(s) : pp 606 - 617 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] Abies alba
[Termes IGN] arbre (flore)
[Termes IGN] arbre mort
[Termes IGN] croissance des arbres
[Termes IGN] diamètre des arbres
[Termes IGN] données dendrométriques
[Termes IGN] dynamique de la végétation
[Termes IGN] Europe centrale
[Termes IGN] Fagus sylvatica
[Termes IGN] forêt
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] Larix decidua
[Termes IGN] modèle de croissance végétale
[Termes IGN] modèle de simulation
[Termes IGN] mortalité
[Termes IGN] Picea abies
[Termes IGN] Pinus cembra
[Termes IGN] prévision
[Termes IGN] Quercus (genre)
[Termes IGN] SuisseRésumé : (auteur) Tree mortality is caused by complex interactions between multiple biotic and abiotic factors. Processes of tree mortality that are not induced by natural disturbances are often reflected in distinct radial growth patterns of trees, which typically serve as reliable indicators of impending tree mortality. However, it remains unclear whether empirical mortality models that are based on tree size and growth result in more realistic projections of forest succession in dynamic vegetation models (DVMs). We used a combination of tree-ring and inventory data from unmanaged Swiss natural forest reserves to derive species-specific survival models for six Central European tree species (Abies alba, Fagus sylvatica, Larix decidua, Picea abies, Pinus cembra and Quercus spp.). We jointly used 528 tree-ring samples and inventory data from eight forest reserves. We implemented the estimated parameters of the survival models into the DVM ForClim and performed simulations of forest succession that were validated using the inventory data of the forest reserves. Size- and growth-dependent variables (i.e., diameter at breast height and mean ring width) over the last few years prior to tree death were reliable predictors to distinguish between dying and living trees. Very low mean ring widths over several preceding years as well as small and large trees, respectively, reflected low survival probabilities. However, the small sample sizes of small and large trees resulted in considerable uncertainty of the survival probabilities. The implementation of these survival models in ForClim yielded plausible projections in short-term simulations and for some sites improved the predictions compared to the current ForClim version. Stand basal area, however, tended to be overestimated. Long-term simulations of ForClim based on the empirical survival models resulted in realistic predictions only if the uncertainty of the predicted survival probabilities was considered. We conclude that the combination of different data sources in combination with the consideration of intra-specific trait variability yields robust predictions of tree survival probabilities, thus paving the way towards better tree mortality models and more reliable projections of future forest dynamics. Numéro de notice : A2019-009 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1016/j.foreco.2018.11.042 Date de publication en ligne : 29/11/2018 En ligne : https://doi.org/10.1016/j.foreco.2018.11.042 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=91603
in Forest ecology and management > vol 433 (15 February 2019) . - pp 606 - 617[article]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 Un algorithme pour battre le record du SwissTrainChallenge : poser le pied dans chacun des 26 cantons le plus rapidement possible en utilisant uniquement des transports publics / Emmanuel Clédat in XYZ, n° 157 (décembre 2018 - février 2019)PermalinkAutomated Swiss-style relief shading and rock hachuring / Roman Geisthövel in Cartographic journal (the), Vol 55 n° 4 (November 2018)PermalinkComparing historical and contemporary maps : a methodological framework for a cartographic map comparison applied to Swiss maps / Christin Loran in International journal of geographical information science IJGIS, vol 32 n° 11-12 (November - December 2018)PermalinkOpenGIS.ch : QGis au pays du gruyère / Marco Bernasocchi in Géomatique expert, n° 125 (novembre - décembre 2018)PermalinkLa propriété en 3D : état des lieux / Anonyme in Géomatique expert, n° 123 (juillet - août 2018)PermalinkExtracting leaf area index using viewing geometry effects : A new perspective on high-resolution unmanned aerial system photography / Lukas Roth in ISPRS Journal of photogrammetry and remote sensing, vol 141 (July 2018)PermalinkGenève 1850, du plan-relief Magnin à la visite virtuelle / David Desbuisson in XYZ, n° 155 (juin - août 2018)PermalinkAre prominent mountains frequently mentioned in text? Exploring the spatial expressiveness of text frequency / Curdin Derungs in International journal of geographical information science IJGIS, vol 32 n° 5-6 (May - June 2018)PermalinkRemotely sensed forest habitat structures improve regional species conservation / Christian Reichsteiner in Remote sensing in ecology and conservation, vol 3 n° 4 (December 2017)PermalinkA simulation and visualization environment for spatiotemporal disaster risk assessments of network infrastructures / Magnus Heittzler in Cartographica, vol 52 n° 4 (Winter 2017)Permalink