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Discovering non-compliant window co-occurrence patterns / Reem Y. Ali in Geoinformatica, vol 21 n° 4 (October - December 2017)
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Titre : Discovering non-compliant window co-occurrence patterns Type de document : Article/Communication Auteurs : Reem Y. Ali, Auteur ; Venkata M. V. Gunturi, Auteur ; Andrew J. Kotz, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 829 - 866 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique
[Termes IGN] exploration de données géographiques
[Termes IGN] géostatistique
[Termes IGN] matrice de co-occurrence
[Termes IGN] reconstruction d'itinéraire ou de trajectoire
[Termes IGN] transportRésumé : (Auteur) Given a set of trajectories annotated with measurements of physical variables, the problem of Non-compliant Window Co-occurrence (NWC) pattern discovery aims to determine temporal signatures in the explanatory variables which are highly associated with windows of undesirable behavior in a target variable. NWC discovery is important for societal applications such as eco-friendly transportation (e.g. identifying engine signatures leading to high greenhouse gas emissions). Challenges of designing a scalable algorithm for NWC discovery include the non-monotonicity of popular spatio-temporal statistical interest measures of association such as the cross-K function which renders the anti-monotone pruning based algorithms (e.g. Apriori) inapplicable for such interest measures. In our preliminary work, we proposed two upper bounds for the cross-K function and a top-down multi-parent tracking approach that uses these bounds for filtering out uninteresting candidate patterns and then applies a minimum support (i.e. frequency) threshold as a post-processing step to filter out chance patterns. In this paper, we propose a novel bi-directional pruning approach (BDNMiner) that combines top-down pruning based on the cross-K function threshold with bottom-up pruning based on the minimum support threshold to efficiently mine NWC patterns. Case studies with real world engine data demonstrates the ability of the proposed approach to discover patterns which are interesting to engine scientists. Experimental evaluation on real-world data show that the proposed approach yields substantial computational savings compared to prior work. Numéro de notice : A2017-605 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1007/s10707-016-0289-3 En ligne : https://doi.org/10.1007/s10707-016-0289-3 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86915
in Geoinformatica > vol 21 n° 4 (October - December 2017) . - pp 829 - 866[article]Enhancing plant diversity and mitigating BVOC emissions of urban green spaces through the introduction of ornamental tree species / Yuan Ren in Urban Forestry & Urban Greening, vol 27 (October 2017)
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Titre : Enhancing plant diversity and mitigating BVOC emissions of urban green spaces through the introduction of ornamental tree species Type de document : Article/Communication Auteurs : Yuan Ren, Auteur ; Ying Ge, Auteur ; Danping Ma, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 305 - 313 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] arbre urbain
[Termes IGN] biodiversité
[Termes IGN] espace vert
[Termes IGN] milieu urbain
[Termes IGN] ozone
[Termes IGN] pollution atmosphérique
[Termes IGN] service écosystémique
[Termes IGN] urbanisme
[Termes IGN] ville
[Vedettes matières IGN] Economie forestièreRésumé : (auteur) Promoting the plant diversity of urban green spaces is crucial to increase ecosystem services in urban areas. While introducing ornamental plants can enhance the biodiversity of green spaces it risks environmental impacts such as increasing emissions of biogenic volatile organic compounds (BVOCs) that are harmful to air quality and human health. The present study, taking Qingdao City as a case study, evaluated the plant diversity and BVOC emissions of urban green spaces and tried to find out a solution to increase biodiversity while reducing BVOC emissions. Results showed that: (1) the species diversity and phylogenetic diversity of trees in urban green spaces were 22% and 16% lower than rural forest of this region; (2) urban areas had higher BVOC emission intensity (2.6 g C m−2 yr−1) than their rural surroundings (2.1 g C m−2 yr−1); (3) introducing the selected 11 tree species will increase 15% and 11% of species diversity and phylogenetic diversity, respectively; and (4) the BVOC emissions from green spaces will more than triple by 2050, but a moderate introduction of the selected low-emitting trees species could reduce 34% of these emissions. The scheme of introducing low-emitting ornamental species leads to a win–win situation and also has implications for the sustainable green space management of other cities. Numéro de notice : A2017-560 Affiliation des auteurs : non IGN Thématique : BIODIVERSITE/FORET Nature : Article DOI : 10.1016/j.ufug.2017.08.011 En ligne : https://doi.org/10.1016/j.ufug.2017.08.011 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86639
in Urban Forestry & Urban Greening > vol 27 (October 2017) . - pp 305 - 313[article]Evaluation of NTCM-BC and a proposed modification for single-frequency positioning / Xiaohong Zhang in GPS solutions, vol 21 n° 4 (October 2017)
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Titre : Evaluation of NTCM-BC and a proposed modification for single-frequency positioning Type de document : Article/Communication Auteurs : Xiaohong Zhang, Auteur ; Fujian Ma, Auteur ; Xiaodong Ren, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 1535 - 1548 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement du signal
[Termes IGN] atténuation du signal
[Termes IGN] modèle ionosphérique
[Termes IGN] Neustrelitz TEC model NTCM
[Termes IGN] positionnement par GNSS
[Termes IGN] récepteur monofréquence
[Termes IGN] teneur totale en électronsRésumé : (Auteur) Ionospheric delay is a dominant factor that affects the accuracy of single-frequency positioning. Thus, an empirical ionospheric model with high accuracy is very important for single-frequency users. This study proposes a modified empirical broadcast ionospheric model, called MNTCM-BC, based on the Neustrelitz Total Electron Content (TEC) broadcast model NTCM-BC. Nine daily ionospheric coefficients of these models are estimated using datasets of the previous day from 30 globally distributed Global Navigation Satellite System monitor stations, and the prediction performance of the MNTCM-BC is evaluated with the datasets of the current day from all 300 verification stations. The results show that the complex behavior of the ionosphere is well described by the MNTCM-BC, including the visibility of two ionization crests on both sides of the geomagnetic equator and the TEC variations that depend on the local time and geomagnetic latitude. In terms of the prediction accuracy, compared with the NTCM-BC, the main improvement in the MNTCM-BC is achieved in summer, whereas the accuracy is comparable in other seasons. Hence, the following analyses are focused on summer. In the low-solar activity year of 2009, the prediction accuracy of the MNTCM-BC is improved by 0.11 TECU compared with that of the NTCM-BC. As to the high-solar activity year of 2014, the corresponding improvement is 0.35 TECU. In addition, when the number of monitor stations is increased from 30 to 300, the prediction accuracy of two models can be slightly improved by 0.06 TECU in 2009 and 0.13 TECU in 2014, respectively, while reliability enhances. Furthermore, the average three-dimensional positioning accuracy of 160 globally distributed stations for single-frequency point positioning using the Klobuchar model, the NTCM-BC and the MNTCM-BC is 1.83, 1.21 and 1.20 m during quiet day and 3.15, 2.31 and 2.21 m during perturbed day, respectively. Relative to the Klobuchar model and the NTCM-BC, the average accuracy improvements in the MNTCM-BC are about 30 and 3%, respectively. Numéro de notice : A2017-615 Affiliation des auteurs : non IGN Thématique : POSITIONNEMENT Nature : Article DOI : 10.1007/s10291-017-0631-8 En ligne : https://doi.org/10.1007/s10291-017-0631-8 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86925
in GPS solutions > vol 21 n° 4 (October 2017) . - pp 1535 - 1548[article]Geometric quality assessment of trajectory-generated VGI road networks based on the symmetric arc similarity / Yan Lyu in Transactions in GIS, vol 21 n° 5 (October 2017)
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Titre : Geometric quality assessment of trajectory-generated VGI road networks based on the symmetric arc similarity Type de document : Article/Communication Auteurs : Yan Lyu, Auteur ; Yehua Sheng, Auteur ; Ningning Guo, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 984 - 1009 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Bases de données localisées
[Termes IGN] analyse comparative
[Termes IGN] données localisées des bénévoles
[Termes IGN] précision des données
[Termes IGN] qualité des données
[Termes IGN] réalité de terrain
[Termes IGN] réseau routier
[Termes IGN] similitudeRésumé : (Auteur) As large amounts of trajectories from a wide variety of Volunteered Geographic Information (referred to as VGI) contributors pour into the spatial database, the geometric qualities of the VGI road networks generated from these trajectories are different from the ground truth road dataset and so need to be differently assessed. To address this issue, an assessment approach based on symmetric arc similarity is proposed, and the geometric quality of a VGI road network is assessed by its conformity with the corresponding ground truth road network, the results being visualized as hierarchical thematic maps. To compute the conformity, the geometric similarity between the VGI road arc and the corresponding ground truth road arc, which is selected by the adaptive searching distance, is measured based on the symmetric arc similarity method; the geometric quality is assessed based on an assessment matrix. Also, the symmetric arc similarity method is independent of directions and with a feature of shift-independence, which is applicable to assess the geometric qualities of different VGI road networks and makes the assessment result consistent with the actual situation of the real world. The robustness and scalability of the approach are examined using VGI road networks from different sources. Numéro de notice : A2017-633 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1111/tgis.12256 En ligne : http://dx.doi.org/10.1111/tgis.12256 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86952
in Transactions in GIS > vol 21 n° 5 (October 2017) . - pp 984 - 1009[article]Hyperspectral dimensionality reduction for biophysical variable statistical retrieval / Juan Pablo Rivera-Caicedo in ISPRS Journal of photogrammetry and remote sensing, vol 132 (October 2017)
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Titre : Hyperspectral dimensionality reduction for biophysical variable statistical retrieval Type de document : Article/Communication Auteurs : Juan Pablo Rivera-Caicedo, Auteur ; Jochem Verrelst, Auteur ; Jordi Munoz-Mari, Auteur ; et al., Auteur Année de publication : 2017 Article en page(s) : pp 88 - 101 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] image HYMAP
[Termes IGN] image hyperspectrale
[Termes IGN] Leaf Area Index
[Termes IGN] régression linéaire
[Termes IGN] variable biophysique (végétation)Résumé : (Auteur) Current and upcoming airborne and spaceborne imaging spectrometers lead to vast hyperspectral data streams. This scenario calls for automated and optimized spectral dimensionality reduction techniques to enable fast and efficient hyperspectral data processing, such as inferring vegetation properties. In preparation of next generation biophysical variable retrieval methods applicable to hyperspectral data, we present the evaluation of 11 dimensionality reduction (DR) methods in combination with advanced machine learning regression algorithms (MLRAs) for statistical variable retrieval. Two unique hyperspectral datasets were analyzed on the predictive power of DR + MLRA methods to retrieve leaf area index (LAI): (1) a simulated PROSAIL reflectance data (2101 bands), and (2) a field dataset from airborne HyMap data (125 bands). For the majority of MLRAs, applying first a DR method leads to superior retrieval accuracies and substantial gains in processing speed as opposed to using all bands into the regression algorithm. This was especially noticeable for the PROSAIL dataset: in the most extreme case, using the classical linear regression (LR), validation results (RMSECV) improved from 0.06 (12.23) without a DR method to 0.93 (0.53) when combining it with a best performing DR method (i.e., CCA or OPLS). However, these DR methods no longer excelled when applied to noisy or real sensor data such as HyMap. Then the combination of kernel CCA (KCCA) with LR, or a classical PCA and PLS with a MLRA showed more robust performances ( of 0.93). Gaussian processes regression (GPR) uncertainty estimates revealed that LAI maps as trained in combination with a DR method can lead to lower uncertainties, as opposed to using all HyMap bands. The obtained results demonstrated that, in general, biophysical variable retrieval from hyperspectral data can largely benefit from dimensionality reduction in both accuracy and computational efficiency. Numéro de notice : A2017-640 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.isprsjprs.2017.08.012 En ligne : https://doi.org/10.1016/j.isprsjprs.2017.08.012 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=86995
in ISPRS Journal of photogrammetry and remote sensing > vol 132 (October 2017) . - pp 88 - 101[article]Exemplaires(3)
Code-barres Cote Support Localisation Section Disponibilité 081-2017101 RAB Revue Centre de documentation En réserve L003 Disponible 081-2017102 DEP-EAF Revue Nancy Dépôt en unité Exclu du prêt 081-2017103 DEP-EXM Revue Saint-Mandé Dépôt en unité Exclu du prêt Hyperspectral UAV-imagery and photogrammetric canopy height model in estimating forest stand variables / Sakari Tuominen in Silva fennica, vol 51 n° 5 (2017)
PermalinkInitial assessment of the COMPASS/BeiDou-3 : new-generation navigation signals / Xiaohong Zhang in Journal of geodesy, vol 91 n° 10 (October 2017)
PermalinkKnowledge extraction from crowdsourced data for the enrichment of road networks / Gregor Jossé in Geoinformatica, vol 21 n° 4 (October - December 2017)
PermalinkMobile precise trigonometric levelling system based on land vehicle: an alternative method for precise levelling / J. Zou in Survey review, vol 49 n° 355 (October 2017)
PermalinkThe potential of multifrequency SAR images for estimating forest biomass in Mediterranean areas / Emanuele Santi in Remote sensing of environment, vol 200 (October 2017)
PermalinkTowards a multi-scale approach for an Earth observation-based assessment of natural resource exploitation in conflict regions / Elisabeth Schoepfer in Geocarto international, vol 32 n° 10 (October 2017)
PermalinkUncertain Voronoi cell computation based on space decomposition / Klaus Arthur Schmid in Geoinformatica, vol 21 n° 4 (October - December 2017)
PermalinkVariance of light-related foliar traits across spatial and temporal scales in the Mediterranean evergreen Olea europaea L. / Adrián G. Escribano-Rocafort in Perspectives in Plant Ecology, Evolution and Systematics, vol 28 (October 2017)
Permalinkvol IV-2/W4 - September 2017 - ISPRS Geospatial Week 2017, 18–22 September, Wuhan, China (Bulletin de ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences) / D. Li
PermalinkAtmospheric correction over coastal waters using multilayer neural networks / Yongzhen Fan in Remote sensing of environment, vol 199 (15 September 2017)
PermalinkExamination of Sentinel-2A multi-spectral instrument (MSI) reflectance anisotropy and the suitability of a general method to normalize MSI reflectance to nadir BRDF adjusted reflectance / David P. Roy in Remote sensing of environment, vol 199 (15 September 2017)
PermalinkUnderstanding the temporal behavior of crops using Sentinel-1 and Sentinel-2-like data for agricultural applications / Amanda Veloso in Remote sensing of environment, vol 199 (15 September 2017)
PermalinkAssimilation de données géodésiques et estimation de références pour l’étude du changement climatique – Présentation du projet ANR GEODESIE / David Coulot in XYZ, n° 152 (septembre - novembre 2017)
PermalinkBand subset selection for anomaly detection in hyperspectral imagery / Lin Wang in IEEE Transactions on geoscience and remote sensing, vol 55 n° 9 (September 2017)
PermalinkBiodiversity effects on ecosystem functioning in a 15-year grassland experiment: patterns, mechanisms, and open questions / Wolfgang W. Weisser in Basic and Applied Ecology, vol 23 (September 2017)
PermalinkComparison of precise orbit determination methods of zero-difference kinematic, dynamic and reduced-dynamic of GRACE-A satellite using SHORDE software / Kai Li in Journal of applied geodesy, vol 11 n° 3 (September 2017)
PermalinkConsumer mass market accelerometers for GNSS anti-spoofing / Sherman Lo in Inside GNSS, vol 12 n° 5 (September - October 2017)
PermalinkCrowdsourcing a cyclist perspective on suggested recreational paths in real-world networks / Kevin Baker in Cartography and Geographic Information Science, Vol 44 n° 5 (September 2017)
PermalinkCrown bulk density and fuel moisture dynamics in Pinus pinaster stands are neither modified by thinning nor captured by the Forest Fire Weather Index / Marc Soler Martin in Annals of Forest Science, vol 74 n° 3 (September 2017)
PermalinkDenoising of natural images through robust wavelet thresholding and genetic programming / Asem Khmag in The Visual Computer, vol 33 n°9 (September 2017)
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