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Mapping spatial distribution of forest age in China / Yuan Zhang in Earth and space science, vol 4 n° 3 (March 2017)
[article]
Titre : Mapping spatial distribution of forest age in China Type de document : Article/Communication Auteurs : Yuan Zhang, Auteur ; Yitong Yao, Auteur ; Xuhui Wang, Auteur ; Yongwen Liu, Auteur ; Shilong Piao, Auteur Année de publication : 2017 Article en page(s) : pp 108 - 116 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Végétation
[Termes IGN] carte forestière
[Termes IGN] Chine
[Termes IGN] Cupressaceae
[Termes IGN] distribution spatiale
[Termes IGN] données lidar
[Termes IGN] données localisées 3D
[Termes IGN] forêt ancienne
[Termes IGN] hauteur des arbres
[Termes IGN] incertitude des données
[Termes IGN] inventaire forestier (techniques et méthodes)
[Termes IGN] inventaire forestier étranger (données)
[Termes IGN] peuplement forestier
[Termes IGN] Pinophyta
[Termes IGN] Pinus massoniana
[Termes IGN] puits de carboneRésumé : (auteur) Forest stand age is a meaningful metric, which reflects the past disturbance legacy, provides guidelines for forest management practices, and is an important factor in qualifying forest carbon cycles and carbon sequestration potential. Reliable large-scale forest stand age information with high spatial resolutions, however, is difficult to obtain. In this study, we developed a top-down method to downscale the provincial statistics of national forest inventory data into 1 km stand age map using climate data and light detection and ranging-derived forest height. We find that the distribution of forest stand age in China is highly heterogeneous across the country, with a mean value of ~42.6 years old. The relatively young stand age for Chinese forests is mostly due to the large proportion of newly planted forests (0–40 years old), which are more prevailing in south China. Older forests (stand age > 60 years old) are more frequently found in east Qinghai-Tibetan Plateau and the central mountain areas of west and northeast China, where human activities are less intensive. Among the 15 forest types, forests dominated by species of , with the exception of Cunninghamia lanceolata stands, have the oldest mean stand age (136 years), whereas Pinus massoniana forests are the youngest (18 years). We further identified uncertainties associated with our forest age map, which are high in west and northeast China. Our work documents the distribution of forest stand age in China at a high resolution which is useful for carbon cycle modeling and the sustainable use of China's forest resources. Numéro de notice : A2107-277 Affiliation des auteurs : non IGN Thématique : FORET Nature : Article DOI : 10.1002/2016EA000177 En ligne : https://doi.org/10.1002/2016EA000177 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=85298
in Earth and space science > vol 4 n° 3 (March 2017) . - pp 108 - 116[article]
Titre : An adaptive approach for interlinking georeferenced data Type de document : Article/Communication Auteurs : Abdelfettah Feliachi , Auteur ; Nathalie Abadie , Auteur ; Fayçal Hamdi , Auteur Editeur : New York [Etats-Unis] : Association for computing machinery ACM Année de publication : 2017 Projets : 1-Pas de projet / Conférence : K-CAP 2017, 9th international conference on knowledge capture 04/12/2017 06/12/2017 Austin Texas - Etats-Unis Proceedings ACM Importance : 8 p. Format : 21 x 30 cm Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] incertitude des données
[Termes IGN] modèle géométrique
[Termes IGN] précision de localisation
[Termes IGN] qualité des données
[Termes IGN] web des donnéesRésumé : (auteur) The resources published on the Web of data are often described by spatial references such as coordinates. The common data linking approaches are mainly based on the hypothesis that spatially close resources are more likely to represent the same thing. However, this assumption is valid only when the spatial references that are compared have been produced with the same positional accuracy, and when they actually represent the same spatial characteristic of the resources captured in an unambiguous way. Otherwise, spatial distance-based matching algorithms may produce erroneous links. In this article, we first suggest to formalize and acquire the knowledge about the spatial references, namely their positional accuracy, their geometric modeling, their level of detail, and the vagueness of the spatial entities they represent. We then propose an interlinking approach that dynamically adapts the way spatial references are compared, based on this knowledge. Numéro de notice : C2017-024 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Autre URL associée : vers HAL Thématique : GEOMATIQUE/INFORMATIQUE Nature : Communication nature-HAL : ComAvecCL&ActesPubliésIntl DOI : 10.1145/3148011.3148025 Date de publication en ligne : 20/12/2017 En ligne : https://doi.org/10.1145/3148011.3148025 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=89286 Evaluating the effect of visually represented geodata uncertainty on decision-making: systematic review, lessons learned, and recommendations / Christoph Kinkeldey in Cartography and Geographic Information Science, Vol 44 n° 1 (January 2017)
[article]
Titre : Evaluating the effect of visually represented geodata uncertainty on decision-making: systematic review, lessons learned, and recommendations Type de document : Article/Communication Auteurs : Christoph Kinkeldey, Auteur ; Alan M. MacEachren, Auteur ; Maria Riveiro, Auteur ; Jochen Schiewe, Auteur Année de publication : 2017 Article en page(s) : pp 1 - 21 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] aide à la décision
[Termes IGN] incertitude des données
[Termes IGN] information géographique
[Termes IGN] visualisation de données
[Vedettes matières IGN] GéovisualisationRésumé : (auteur) For many years, uncertainty visualization has been a topic of research in several disparate fields, particularly in geographical visualization (geovisualization), information visualization, and scientific visualization. Multiple techniques have been proposed and implemented to visually depict uncertainty, but their evaluation has received less attention by the research community. In order to understand how uncertainty visualization influences reasoning and decision-making using spatial information in visual displays, this paper presents a comprehensive review of uncertainty visualization assessments from geovisualization and related fields. We systematically analyze characteristics of the studies under review, i.e., number of participants, tasks, evaluation metrics, etc. An extensive summary of findings with respect to the effects measured or the impact of different visualization techniques helps to identify commonalities and differences in the outcome. Based on this summary, we derive “lessons learned” and provide recommendations for carrying out evaluation of uncertainty visualizations. As a basis for systematic evaluation, we present a categorization of research foci related to evaluating the effects of uncertainty visualization on decision-making. By assigning the studies to categories, we identify gaps in the literature and suggest key research questions for the future. This paper is the second of two reviews on uncertainty visualization. It follows the first that covers the communication of uncertainty, to investigate the effects of uncertainty visualization on reasoning and decision-making. Numéro de notice : A2017-098 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2015.1089792 En ligne : http://dx.doi.org/10.1080/15230406.2015.1089792 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=84477
in Cartography and Geographic Information Science > Vol 44 n° 1 (January 2017) . - pp 1 - 21[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 032-2017011 RAB Revue Centre de documentation En réserve L003 Disponible Bounding the integer bootstrapped GNSS baseline’s tail probability in the presence of stochastic uncertainty / Steven E. Langel in Journal of geodesy, vol 90 n° 11 (November 2016)
[article]
Titre : Bounding the integer bootstrapped GNSS baseline’s tail probability in the presence of stochastic uncertainty Type de document : Article/Communication Auteurs : Steven E. Langel, Auteur ; Samer M. Khanafseh, Auteur ; Boris Pervan, Auteur Année de publication : 2016 Article en page(s) : pp 1293 - 1305 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géodésie spatiale
[Termes IGN] corrélation
[Termes IGN] incertitude des données
[Termes IGN] ligne de base
[Termes IGN] positionnement par GNSSRésumé : (Auteur) Differential carrier phase applications that utilize cycle resolution need the probability density function of the baseline estimate to quantify its region of concentration. For the integer bootstrap estimator, the density function has an analytical definition that enables probability calculations given perfect statistical knowledge of measurement and process noise. This paper derives a method to upper bound the tail probability of the integer bootstrapped GNSS baseline when the measurement and process noise correlation functions are unknown, but can be upper and lower bounded. The tail probability is shown to be a non-convex function of a vector of conditional variances, whose feasible region is a convex polytope. We show how to solve the non-convex optimization problem globally by discretizing the polytope into small hyper-rectangular elements, and demonstrate the method for a static baseline estimation problem. Numéro de notice : A2016-803 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s00190-016-0923-8 Date de publication en ligne : 13/06/2016 En ligne : http://dx.doi.org/ 10.1007/s00190-016-0923-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82588
in Journal of geodesy > vol 90 n° 11 (November 2016) . - pp 1293 - 1305[article]Incorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections? / Paul Holloway in International journal of geographical information science IJGIS, vol 30 n° 9-10 (September - October 2016)
[article]
Titre : Incorporating movement in species distribution models: how do simulations of dispersal affect the accuracy and uncertainty of projections? Type de document : Article/Communication Auteurs : Paul Holloway, Auteur ; Jennifer A. Miller, Auteur ; Simon Gillings, Auteur Année de publication : 2016 Article en page(s) : pp 2050 - 2074 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale
[Termes IGN] Aves
[Termes IGN] changement climatique
[Termes IGN] distribution spatiale
[Termes IGN] Grande-Bretagne
[Termes IGN] habitat d'espèce
[Termes IGN] incertitude des données
[Termes IGN] modèle de dispersion
[Termes IGN] système d'information géographiqueRésumé : (Auteur) Species distribution models (SDMs) are one of the most important GIScience research areas in biogeography and are the primary means by which the potential effects of climate change on species’ distributions and ranges are investigated. Dispersal is an important ecological process for species responding to changing climates, however, SDMs and their subsequent spatial products rarely reflect accessibility to any future suitable environment. Dispersal-related movement can be confounded by factors that vary across landscapes and climates, as well as within and among species, and it has therefore remained difficult to parametrise in SDMs. Here we compared 20 models that have previously been used (or have the potential to be used) to represent dispersal processes in SDM to predict future range shifts in response to climate change. We assessed the different dispersal models in terms of their accuracy at predicting future distributions, as well as the uncertainty associated with their predictions. Atlas data for 50 bird species from 1988 to 1991 in Great Britain were treated as base distributions (t1), with the species–environment relationships extrapolated (using three commonly used statistical methods) to 2008–2011 (t2). Dispersal (in the form of the 20 different models) was simulated from the base distribution (t1) to 2008–2011 (t2). The results were then combined and used to identify locations that were both abiotically suitable (obtained from the statistical methods) and accessible (obtained from the dispersal models). The accuracy of these coupled projections was assessed with the 2008–2011 atlas data (the observed t2 distribution). There was substantial variation in the accuracy of the different dispersal models, and in general, the more restrictive dispersal models (e.g. fixed rate dispersal) resulted in lower accuracy for the metrics which reward correct prediction of presences. Ensemble models of the dispersal methods (generated by combining multiple projection outcomes) were created for each species, and a new Ensemble Agreement Index (EAI), which ranges from 0 (no agreement among models) to 1 (full agreement among models) was developed to quantify uncertainty among the projections. EAI values ranged from 0.634 (some areas of disagreement and therefore medium uncertainty among dispersal models) to 0.999 (large areas of agreement and low uncertainty among dispersal models). The results of this research highlight the importance of incorporating dispersal and also illustrate that the method with which dispersal is simulated greatly impacts the projected future distribution. This has important implications for studies aimed at predicting the effects of changing environmental conditions on species’ distributions. Numéro de notice : A2016-575 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2016.1158823 En ligne : http://dx.doi.org/10.1080/13658816.2016.1158823 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=81732
in International journal of geographical information science IJGIS > vol 30 n° 9-10 (September - October 2016) . - pp 2050 - 2074[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 079-2016051 RAB Revue Centre de documentation En réserve L003 Disponible Propagating uncertainty through individual tree volume model predictions to large-area volume estimates / Ronald E. McRoberts in Annals of Forest Science, vol 73 n° 3 (September 2016)PermalinkEvaluating the impact of visualization of wildfire hazard upon decision-making under uncertainty / Lisa Cheong in International journal of geographical information science IJGIS, vol 30 n° 7- 8 (July - August 2016)PermalinkGeographically weighted evidence combination approaches for combining discordant and inconsistent volunteered geographical information / Alexis Comber in Geoinformatica, vol 20 n° 3 (July - September 2016)PermalinkApproximating prediction uncertainty for random forest regression models / John W. Coulston in Photogrammetric Engineering & Remote Sensing, PERS, vol 82 n° 3 (March 2016)PermalinkA correctly weighted least squares adjustment - Part 2 Estimating uncertainties / Charles D. Ghilani in xyHt, vol 2016 n° 2 (February 2016)PermalinkLa géostatistique : une vision novatrice au service des géosciences / Bernard Bourgine in Géosciences, n°20 (février 2016)PermalinkObserved changes in the Earth’s dynamic oblateness from GRACE data and geophysical models / Y. Sun in Journal of geodesy, vol 90 n° 1 (January 2016)PermalinkQualité des données géographiques : à propos de la propagation des incertitudes / Gilles Troispoux in Signature, n° 59 (janvier 2016)PermalinkUncertainty modelling and quality control for spatial data / Wenzhong Shi (2016)PermalinkVisualisation and evaluation of flood uncertainties based on ensemble modelling / N. J. Lim in International journal of geographical information science IJGIS, vol 30 n° 1-2 (January - February 2016)PermalinkIntégration de l’imperfection de l’information dans les dynamiques spatiales. Définitions, outils et exemples / Eric Desjardin in Revue internationale de géomatique, vol 25 n° 3 (septembre - novembre 2015)PermalinkRecommendations for the use of tree models to estimate national forest biomass and assess their uncertainty / Matieu Henry in Annals of Forest Science, vol 72 n° 6 (September 2015)PermalinkMapping uncertainty from multi-criteria analysis of land development suitability, the case of Howth, Dublin / Bernadette Quinn in Journal of maps, vol 11 n° 3 ([01/07/2015])PermalinkNetwork-based estimation of time-dependent noise in GPS position time series / Ksenia Dimitrieva in Journal of geodesy, vol 89 n° 6 (June 2015)PermalinkBayesian belief networks as a versatile method for assessing uncertainty in land-change modeling / Carsten Krüger in International journal of geographical information science IJGIS, vol 29 n° 1 (January 2015)PermalinkGeo-spatial modelling with unbalanced data: modelling the spatial pattern of human activity during the Stone Age / Jaroslav Jasiewicz in Open geosciences, vol 7 n° 1 (January 2015)PermalinkVariance component estimation uncertainty for unbalanced data: application to a continent-wide vertical datum / M. S. Filmer in Journal of geodesy, vol 88 n° 11 (November 2014)PermalinkMulti-view 3D circular target reconstruction with uncertainty analysis / Bahman Soheilian in ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, vol II-3 (September 2014)PermalinkActive learning in the spatial domain for remote sensing image classification / André Stumpf in IEEE Transactions on geoscience and remote sensing, vol 52 n° 5 tome 1 (May 2014)PermalinkModeling vague spatial data warehouses using the VSCube conceptual model / Thiago Luís Lopes-Siqueira in Geoinformatica, vol 18 n° 2 (April 2014)Permalink