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Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval / Jochem Verrlest in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)
[article]
Titre : Gaussian processes uncertainty estimates in experimental Sentinel-2 LAI and leaf chlorophyll content retrieval Type de document : Article/Communication Auteurs : Jochem Verrlest, Auteur ; Juan Pablo Rivera, Auteur ; José Moreno, Auteur ; Gustavo Camps-Valls, Auteur Année de publication : 2013 Article en page(s) : pp 157 - 167 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] algorithme de Gauss
[Termes IGN] apprentissage automatique
[Termes IGN] chlorophylle
[Termes IGN] image Sentinel-MSI
[Termes IGN] incertitude des données
[Termes IGN] indice foliaire
[Termes IGN] Leaf Area Index
[Termes IGN] régression
[Termes IGN] surveillance de la végétation
[Termes IGN] teneur en chlorophylle des feuilles
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) ESA’s upcoming Sentinel-2 (S2) Multispectral Instrument (MSI) foresees to provide continuity to land monitoring services by relying on optical payload with visible, near infrared and shortwave infrared sensors with high spectral, spatial and temporal resolution. This unprecedented data availability leads to an urgent need for developing robust and accurate retrieval methods, which ideally should provide uncertainty intervals for the predictions. Statistical learning regression algorithms are powerful candidats for the estimation of biophysical parameters from satellite reflectance measurements because of their ability to perform adaptive, nonlinear data fitting. In this paper, we focus on a new emerging technique in the field of Bayesian nonparametric modeling. We exploit Gaussian process regression (GPR) for retrieval, which is an accurate method that also provides uncertainty intervals along with the mean estimates. This distinct feature is not shared by other machine learning approaches. In view of implementing the regressor into operational monitoring applications, here the portability of locally trained GPR models was evaluated. Experimental data came from the ESA-led field campaign SPARC (Barrax, Spain). For various simulated S2 configurations (S2-10m, S2-20m and S2-60m) two important biophysical parameters were estimated: leaf chlorophyll content (LCC) and leaf area index (LAI). Local evaluation of an extended training dataset with more variation over bare soil sites led to improved LCC and LAI mapping with reduced uncertainties. GPR reached the 10% precision required by end users, with for LCC a NRMSE of 3.5–9.2% (r2: 0.95–0.99) and for LAI a NRMSE of 6.5–7.3% (r2: 0.95–0.96). The developed GPR models were subsequently applied to simulated Sentinel images over various sites. The associated uncertainty maps proved to be a good indicator for evaluating the robustness of the retrieval performance. The generally low uncertainty intervals over vegetated surfaces suggest that the locally trained GPR models are portable to other sites and conditions. Numéro de notice : A2013-708 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32844
in ISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 157 - 167[article]Géopeuple : Création et analyse de données topographiques et démographiques sur 200 ans / Anne Ruas in Cartes & Géomatique, n° 218 (décembre 2013)
[article]
Titre : Géopeuple : Création et analyse de données topographiques et démographiques sur 200 ans Type de document : Article/Communication Auteurs : Anne Ruas , Auteur ; Christine Plumejeaud, Auteur ; Marie-Christine Vouloir, Auteur ; Lucie Nahassia, Auteur ; Eric Grosso , Auteur ; Ana-Maria Olteanu-Raimond , Auteur ; Claude Motte, Auteur Année de publication : 2013 Projets : GéoPeuple / Ruas, Anne Article en page(s) : pp 17 - 29 Note générale : Bibliographie Langues : Français (fre) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] analyse diachronique
[Termes IGN] base de données cartographiques
[Termes IGN] base de données vectorielles
[Termes IGN] données démographiques
[Termes IGN] données topographiques
[Termes IGN] interface web
[Termes IGN] population
[Termes IGN] raisonnement spatialRésumé : (Auteur) Afin d'optimiser l'apprentissage des SIG dans l'enseignement supérieur des Sciences de la Terre et de l'environnement, nous présentons une recherche en cours dont l'objectif est d'identifier les raisonnements et les concepts qui sous-tendent les processus de cartographie de susceptibilité avec les SIG. En s'appuyant sur des méthodologies d'analyse quantitative et qualitative des données verbales, notre recherche met en évidence les différences de stratégies entre les experts et les étudiants afin de proposer des instructions didactiques qui aident les étudiants à se rapprocher de démarches experts pour la résolution des problèmes spatiaux. Numéro de notice : A2013-723 Affiliation des auteurs : LASTIG COGIT+Ext (2012-2019) Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueNat DOI : sans En ligne : https://hal.archives-ouvertes.fr/hal-00979799 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32859
in Cartes & Géomatique > n° 218 (décembre 2013) . - pp 17 - 29[article]Réservation
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GéopeupleAdobe Acrobat PDF The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques / Chengbin Deng in ISPRS Journal of photogrammetry and remote sensing, vol 86 (December 2013)
[article]
Titre : The use of single-date MODIS imagery for estimating large-scale urban impervious surface fraction with spectral mixture analysis and machine learning techniques Type de document : Article/Communication Auteurs : Chengbin Deng, Auteur ; Changshan Wu, Auteur Année de publication : 2013 Article en page(s) : pp 100 - 110 Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] analyse de mélange spectral d’extrémités multiples
[Termes IGN] analyse des mélanges spectraux
[Termes IGN] apprentissage automatique
[Termes IGN] image multibande
[Termes IGN] image Terra-MODIS
[Termes IGN] méthode des moindres carrés
[Termes IGN] surface imperméable
[Termes IGN] zone urbaineRésumé : (Auteur) Urban impervious surface information is essential for urban and environmental applications at the regional/national scales. As a popular image processing technique, spectral mixture analysis (SMA) has rarely been applied to coarse-resolution imagery due to the difficulty of deriving endmember spectra using traditional endmember selection methods, particularly within heterogeneous urban environments. To address this problem, we derived endmember signatures through a least squares solution (LSS) technique with known abundances of sample pixels, and integrated these endmember signatures into SMA for mapping large-scale impervious surface fraction. In addition, with the same sample set, we carried out objective comparative analyses among SMA (i.e. fully constrained and unconstrained SMA) and machine learning (i.e. Cubist regression tree and Random Forests) techniques. Analysis of results suggests three major conclusions. First, with the extrapolated endmember spectra from stratified random training samples, the SMA approaches performed relatively well, as indicated by small MAE values. Second, Random Forests yields more reliable results than Cubist regression tree, and its accuracy is improved with increased sample sizes. Finally, comparative analyses suggest a tentative guide for selecting an optimal approach for large-scale fractional imperviousness estimation: unconstrained SMA might be a favorable option with a small number of samples, while Random Forests might be preferred if a large number of samples are available. Numéro de notice : A2013-705 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2013.09.010 En ligne : https://doi.org/10.1016/j.isprsjprs.2013.09.010 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32841
in ISPRS Journal of photogrammetry and remote sensing > vol 86 (December 2013) . - pp 100 - 110[article]Using pattern-oriented modeling (POM) to cope with uncertainty in multi-scale agent-based models of land change / Nicholas R. Magliocca in Transactions in GIS, vol 17 n° 6 (December 2013)
[article]
Titre : Using pattern-oriented modeling (POM) to cope with uncertainty in multi-scale agent-based models of land change Type de document : Article/Communication Auteurs : Nicholas R. Magliocca, Auteur ; Erle C. Ellis, Auteur Année de publication : 2013 Article en page(s) : pp 883 - 900 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] aide à la décision
[Termes IGN] changement d'occupation du sol
[Termes IGN] généralisation de base de données
[Termes IGN] incertitude des données
[Termes IGN] occupation du sol
[Termes IGN] représentation multiple
[Termes IGN] système multi-agents
[Termes IGN] utilisation du solRésumé : (Auteur) Local land-use and -cover changes (LUCCs) are the result of both the decisions and actions of individual land-users, and the larger global and regional economic, political, cultural, and environmental contexts in which land-use systems are embedded. However, the dearth of detailed empirical data and knowledge of the influences of global/regional forces on local land-use decisions is a substantial challenge to formulating multi-scale agent-based models (ABMs) of land change. Pattern-oriented modeling (POM) is a means to cope with such process and parameter uncertainty, and to design process-based land change models despite a lack of detailed process knowledge or empirical data. POM was applied to a simplified agent-based model of LUCC to design and test model relationships linking global market influence to agents’ land-use decisions within an example test site. Results demonstrated that evaluating alternative model parameterizations based on their ability to simultaneously reproduce target patterns led to more realistic land-use outcomes. This framework is promising as an agent-based virtual laboratory to test hypotheses of how and under what conditions driving forces of land change differ from a generalized model representation depending on the particular land-use system and location. Numéro de notice : A2013-674 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12012 Date de publication en ligne : 08/01/2013 En ligne : https://doi.org/10.1111/tgis.12012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32810
in Transactions in GIS > vol 17 n° 6 (December 2013) . - pp 883 - 900[article]An inference-based framework to manage data provenance in geoscience applications / Mohammad Rezwanul Huq in IEEE Transactions on geoscience and remote sensing, vol 51 n° 11 (November 2013)
[article]
Titre : An inference-based framework to manage data provenance in geoscience applications Type de document : Article/Communication Auteurs : Mohammad Rezwanul Huq, Auteur ; Peter M.G. Apers, Auteur ; Andreas Wombacher, Auteur Année de publication : 2013 Article en page(s) : pp 5113 - 5130 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Infrastructure de données
[Termes IGN] flux de travaux
[Termes IGN] inférence
[Termes IGN] moteur d'inférence
[Termes IGN] source de données
[Termes IGN] synergiciel
[Termes IGN] traitement de données localiséesRésumé : (Auteur) Data provenance allows scientists to validate their model as well as to investigate the origin of an unexpected value. Furthermore, it can be used as a replication recipe for output data products. However, capturing provenance requires enormous effort by scientists in terms of time and training. First, they need to design the workflow of the scientific model, i.e., workflow provenance, which requires both time and training. However, in practice, scientists may not document any workflow provenance before the model execution due to the lack of time and training. Second, they need to capture provenance while the model is running, i.e., fine-grained data provenance. Explicit documentation of fine-grained provenance is not feasible because of the massive storage consumption by provenance data in the applications, including those from the geoscience domain where data are continuously arriving and are processed. In this paper, we propose an inference-based framework, which provides both workflow and fine-grained data provenance at a minimal cost in terms of time, training, and disk consumption. Our proposed framework is applicable to any given scientific model, and is capable of handling different model dynamics, such as variation in the processing time as well as input data products arrival pattern. Our evaluation of the framework in a real use case with geospatial data shows that the proposed framework is relevant and suitable for scientists in geoscientific domain. Numéro de notice : A2013-613 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1109/TGRS.2013.2247769 En ligne : https://doi.org/10.1109/TGRS.2013.2247769 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=32749
in IEEE Transactions on geoscience and remote sensing > vol 51 n° 11 (November 2013) . - pp 5113 - 5130[article]Réservation
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Code-barres Cote Support Localisation Section Disponibilité 065-2013111 RAB Revue Centre de documentation En réserve L003 Disponible Markov land cover change modeling using pairs of time-series satellite images / Priyakant Sinha in Photogrammetric Engineering & Remote Sensing, PERS, vol 79 n° 11 (November 2013)PermalinkModeling of spatio-temporal dynamics of land use and land cover in a part of Brahmaputra River basin using Geoinformatic techniques / M. Sarabuddin Mondal in Geocarto international, vol 28 n° 7-8 (November - December 2013)PermalinkApport de la télédétection à l'analyse de la dynamique de l'occupation du sol à partir d'une utilisation couplée d'un modèle de markov et d'un automate cellulaire. Cas du département de Sintra (Centre-Ouest de la Cote d'Ivoire). / Vami Hermann N'guessan Bi in Revue Française de Photogrammétrie et de Télédétection, n° 204 (Octobre 2013)PermalinkCity shrinkage simulation: A case study of Katsuura City, Japan / Jianping Gu in Revue internationale de géomatique, vol 23 n° 3 - 4 (septembre 2013 - février 2014)PermalinkContent zooming and information exploration for web and mobile maps. Adaptation of real-time map generalisation to the information seeking strategies of web and mobile users / Pia Bereuter in Revue internationale de géomatique, vol 23 n° 3 - 4 (septembre 2013 - février 2014)PermalinkA data mining approach for evaluation of optimal time-series of MODIS data for land cover mapping at a regional level / Fuqun Zhou in ISPRS Journal of photogrammetry and remote sensing, vol 84 (October 2013)PermalinkGetting closer to everywhere: accurately tracking smartphones indoors / Ramsey Faragher in GPS world, vol 24 n° 10 (October 2013)PermalinkSimulating spatial dynamics and processes in a retail gasoline market: An agent-based modeling approach / Alison J. Heppenstall in Transactions in GIS, vol 17 n° 5 (October 2013)PermalinkA spatial-based KDD process to better manage the river water quality / Hugo Alatrista-Salas in Revue internationale de géomatique, vol 23 n° 3 - 4 (septembre 2013 - février 2014)PermalinkThe signature of self-organisation in cities: Temporal patterns of clustering and growth in street networks / Kinda Al-Sayed in Revue internationale de géomatique, vol 23 n° 3 - 4 (septembre 2013 - février 2014)PermalinkApproche exploratoire SIG pour l'identification des piézomètres représentatifs d'une relation nappe/rivière / Alexandre Brugeron in Géomatique expert, n° 94 (01/09/2013)PermalinkGeneralized composite kernel framework for hyperspectral image classification / J. Li in IEEE Transactions on geoscience and remote sensing, vol 51 n° 9 (September 2013)PermalinkReal-time generalization of point data in mobile and web mapping using quadtrees / Pia Bereuter in Cartography and Geographic Information Science, vol 40 n° 4 (September 2013)PermalinkTemporal logic and operation relations based knowledge representation for land cover change web services / Jun Chen in ISPRS Journal of photogrammetry and remote sensing, vol 83 (September 2013)PermalinkTowards qualitative geovisual analytics: A case study involving places, people, and mediated experience / Ryan Burns in Cartographica, vol 48 n° 3 (October 2013)PermalinkAssessing the veracity of methods for extracting place semantics from Flickr tags / William A Mackaness in Transactions in GIS, vol 17 n° 4 (August 2013)PermalinkFinding science with science: Evaluating a domain and scientific ontology user interface for the discovery of scientific resources / Kristin Stock in Transactions in GIS, vol 17 n° 4 (August 2013)PermalinkA methodological framework for researching the usability of the space-time cube / Irma Kveladze in Cartographic journal (the), vol 50 n° 3 (August 2013)PermalinkTemporal uncertainty in a small area open geodemographic classification / Christopher G. 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