Centre dedocumentation
scientifique

Developing reliably distinguishable color schemes for legends of natural resource taxonomy-based maps / Virgil Vlad in Cartography and Geographic Information Science, Vol 48 n° 5 (September 2021)  

Public [article]  inCartography and Geographic Information Science > Vol 48 n° 5 (September 2021) . - pp 393 - 416 Titre : Developing reliably distinguishable color schemes for legends of natural resource taxonomy-based maps Type de document : Article/Communication Auteurs : Virgil Vlad, Auteur ; Mihai Toti, Auteur ; Sorina Dumitru, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : pp 393 - 416 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Rédaction cartographique [Termes IGN] carte d'occupation du sol [Termes IGN] colorimétrie [Termes IGN] couleur (rédaction cartographique) [Termes IGN] couleur primaire [Termes IGN] lecture de carte [Termes IGN] légende cartographique [Termes IGN] palette de couleurs [Termes IGN] ressources naturelles [Termes IGN] Roumanie [Termes IGN] taxinomie [Termes IGN] visualisation cartographique Résumé : (auteur) The legends of natural resource taxonomy-based maps (e.g. soil, geological, geomorphological, vegetation, and land cover/land use) need many different distinguishable colors. The existing methods of color selection for map legends are based on the designer subjectivity, ensuring schemes having few colors. An analysis of the modeling and management of colors in digital applications has led to define an algorithm to calculate an objective colorimetric measure of color difference – “DE*ab” – based on the perceptually uniform color model CIELAB. The proposed method consists of a set of specific rules for developing hierarchically structured color schemes and a specific procedure for ensuring selection of a large number of reliably distinguishable colors, based on a color difference threshold. The accuracy of color reproduction in printing processes is also taken into account. The method has been applied to develop a standard of colors for soil maps. It contains 63 colors and has been used for developing a soil map having 41 standard colors. A user test of the method results proved that thresholds of 10 DE*ab units and 15 DE*ab units ensure obtaining acceptably distinguishable colors for displaying/printing maps by using high-quality, respectively, current devices. Three datasets that support the research are given. Numéro de notice : A2021-643 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/15230406.2021.1942218 Date de publication en ligne : 23/08/2021 En ligne : https://doi.org/10.1080/15230406.2021.1942218 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=98340 [article]

Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) of wood reveals distinct chemical signatures of two species of Afzelia / Peter Kitin in Annals of Forest Science [en ligne], vol 78 n° 2 (June 2021)  

Public [article]  inAnnals of Forest Science [en ligne] > vol 78 n° 2 (June 2021) . - Article 31 Titre : Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) of wood reveals distinct chemical signatures of two species of Afzelia Type de document : Article/Communication Auteurs : Peter Kitin, Auteur ; Edgard Espinoza, Auteur ; Hans Beeckman, Auteur ; et al., Auteur Année de publication : 2021 Article en page(s) : Article 31 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image [Termes IGN] abattage (sylviculture) [Termes IGN] Afzelia (genre) [Termes IGN] analyse discriminante [Termes IGN] apprentissage non-dirigé [Termes IGN] bois [Termes IGN] espèce végétale [Termes IGN] forêt tropicale [Termes IGN] identification de plantes [Termes IGN] signature spectrale [Termes IGN] spectrométrie [Termes IGN] taxinomie [Termes IGN] temps réel Résumé : (Auteur) Distinct chemical fingerprints of the wood of Afzelia pachyloba and A. bipindensis demonstrated an effective method for identifying these two commercially important species. Direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) allowed high-throughput examination of chemotypes with vast potential in taxonomic, ecological, and forensic research of wood. Context : Afzelia is a genus of valuable tropical timber trees. Accurate identification of wood is required for the prevention of illicit timber trade as well as for certification purposes in the forest and wood products industry. For many years, particular interest has been focused on attempts to distinguish the wood of A. bipindensis Harms from A. pachyloba Harms due to substantial differences in the commercial values of these two species. Aims : We investigated if wood chemical signatures and microscopy could identify the wood of A. bipindensis and A. pachyloba. Methods : We used two approaches, namely metabolome profiling by direct analysis in real-time (DART) time-of-flight mass spectrometry (TOFMS) and wood microstructure by light microscopy and SEM. In all, we analyzed samples from 89 trees of A. bipindensis, and A. pachyloba. Results : The two species could not be separated by the IAWA standard microscopic wood features. SEM analysis showed considerable variation in the morphology of vestured pits; however, this variation was not species-specific. In contrast, DART-TOFMS followed by unsupervised statistics (Discriminant Analysis of Principal Components) showed distinct metabolome signatures of the two species. Conclusion : DART-TOFMS provides a rapid method for wood identification that can be easily applied to small heartwood samples. Time- and cost-effective classification of wood chemotypes by DART-TOFMS can have potential applications in various research questions in forestry, wood science, tree-ecophysiology, and forensics. Numéro de notice : A2021-327 Affiliation des auteurs : non IGN Thématique : FORET/IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1007/s13595-020-01024-1 Date de publication en ligne : 31/03/2021 En ligne : https://doi.org/10.1007/s13595-020-01024-1 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=97488 [article]

Consolidation of crowd-sourced geo-ragged data for parameterized travel recommendations / Ago Luberg (2021)  

Public Titre : Consolidation of crowd-sourced geo-ragged data for parameterized travel recommendations Type de document : Thèse/HDR Auteurs : Ago Luberg, Auteur ; Tanel Tammet, Directeur de thèse Editeur : Tallinn [Estonia] : Tallinn University of Technology Année de publication : 2021 Importance : 159 p. Format : 21 x 30 cm Note générale : bibliographie Dissertation accepted for the defence of the degree of Doctor of Philosophy in Computer Science Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web [Termes IGN] apprentissage automatique [Termes IGN] base de données [Termes IGN] conception orientée utilisateur [Termes IGN] données localisées des bénévoles [Termes IGN] extraction de données [Termes IGN] géoréférencement [Termes IGN] point d'intérêt [Termes IGN] Riga [Termes IGN] site wiki [Termes IGN] système de recommandation [Termes IGN] Tallinn [Termes IGN] taxinomie [Termes IGN] tourisme Résumé : (auteur) The research covered in this thesis is focused on different aspects of the task of creating automated recommendations for tourism, focusing mostly on places of interest like beautiful views, architectural landmarks, charming areas etc. A significant amount of work has been spent on designing and developing actual recommender systems - Sightsplanner, Sightsmap and the automated recommender of Visit Estonia - and their data harvesting methods in order to create a platform for showing the feasibility of the new methods designed and experimented with. The main results of our research are split between three subfields: • Knowledge engineering: we have shown how to formalize fuzzy and uncertain POI categories along with suitable ontologies and reasoner-based algorithms for object matching and score calculation in a real-life context of actual POI-s, available data and easily expressable user preferences. • Machine learning: we have designed a learnable detection system for detecting duplicate POIs from different databases, usable for cross- category, cross-language and cross-city datasets. • We show that learning on Tallinn eateries improved the algorithm parameters to such a degree that on Riga data containing also museums and galleries it gave us 98% accuracy versus 85% accuracy achieved by tuning the algorithm parameters manually. • Knowledge extraction: we have designed an algorithm for high-quality keyword extraction from short crowd-sourced POI descriptions in different languages, able to find a suitable name and to add suitable types to the POI. Our clusterization algorithm is able to merge the POIs based on the extracted data: on the Panoramio and Wikipedia data about U.K. and French locations it was able to find 56% of Wikipedia objects from the textual titles/annotations of Panoramio pictures in the area. Note de contenu : 1- Introduction 2- Related work 3- Involvement in recommender projects 4- Data acquisition and information extraction 5- Data deduplication (using machine learning) 6- Location category and name detection 7- Data storage and object score calculation 8- Conclusions 9- Future work Numéro de notice : 28600 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Thèse étrangère Note de thèse : PhD Thesis : Computer Science : Tallinn University of Technology : 2021 DOI : 10.23658/taltech.23/2021 En ligne : https://doi.org/10.23658/taltech.23/2021 Format de la ressource électronique : URL Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=99407

An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering / Xiaojing Wu in International journal of geographical information science IJGIS, vol 34 n° 9 (September 2020)  

Public [article]  inInternational journal of geographical information science IJGIS > vol 34 n° 9 (September 2020) . - pp 1822 - 1848 Titre : An overview of clustering methods for geo-referenced time series: from one-way clustering to co- and tri-clustering Type de document : Article/Communication Auteurs : Xiaojing Wu, Auteur ; Changxiu Cheng, Auteur ; Raul Zurita-Milla, Auteur Année de publication : 2020 Article en page(s) : pp 1822 - 1848 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] analyse de groupement [Termes IGN] analyse spatio-temporelle [Termes IGN] classification barycentrique [Termes IGN] classification par nuées dynamiques [Termes IGN] exploration de données [Termes IGN] géoréférencement [Termes IGN] modélisation spatio-temporelle [Termes IGN] regroupement de données [Termes IGN] série temporelle [Termes IGN] taxinomie Résumé : (auteur) Even though many studies have shown the usefulness of clustering for the exploration of spatio-temporal patterns, until now there is no systematic description of clustering methods for geo-referenced time series (GTS) classified as one-way clustering, co-clustering and tri-clustering methods. Moreover, the selection of a suitable clustering method for a given dataset and task remains to be a challenge. Therefore, we present an overview of existing clustering methods for GTS, using the aforementioned classification, and compare different methods to provide suggestions for the selection of appropriate methods. For this purpose, we define a taxonomy of clustering-related geographical questions and compare the clustering methods by using representative algorithms and a case study dataset. Our results indicate that tri-clustering methods are more powerful in exploring complex patterns at the cost of additional computational effort, whereas one-way clustering and co-clustering methods yield less complex patterns and require less running time. However, the selection of the most suitable method should depend on the data type, research questions, computational complexity, and the availability of the methods. Finally, the described classification can include novel clustering methods, thereby enabling the exploration of more complex spatio-temporal patterns. Numéro de notice : A2020-477 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2020.1726922 Date de publication en ligne : 16/02/2020 En ligne : https://doi.org/10.1080/13658816.2020.1726922 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95624 [article]

Réservation

Réserver ce document

Exemplaires (1)

Code-barres	Cote	Support	Localisation	Section	Disponibilité
079-2020091	SL	Revue	Centre de documentation	Revues en salle	Disponible

Prediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series / Mathieu Fauvel in Remote sensing of environment, Vol 237 (February 2020)  

Public [article]  inRemote sensing of environment > Vol 237 (February 2020) . - 13 p. Titre : Prediction of plant diversity in grasslands using Sentinel-1 and -2 satellite image time series Type de document : Article/Communication Auteurs : Mathieu Fauvel, Auteur ; Maylis Lopes, Auteur ; Titouan Dubo, Auteur ; Justine Rivers-Moore, Auteur ; Pierre-Louis Frison , Auteur ; Nicolas Gross, Auteur ; Annie Ouin, Auteur Année de publication : 2020 Projets : SEBIOREF / Ouin, Annie Article en page(s) : 13 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image mixte [Termes IGN] biodiversité végétale [Termes IGN] classification par forêts aléatoires [Termes IGN] Haute-Garonne (31) [Termes IGN] image radar moirée [Termes IGN] image RapidEye [Termes IGN] image Sentinel-MSI [Termes IGN] image Sentinel-SAR [Termes IGN] indice de diversité [Termes IGN] indice de végétation [Termes IGN] Normalized Difference Vegetation Index [Termes IGN] prairie [Termes IGN] série temporelle [Termes IGN] taxinomie Résumé : (auteur) The prediction of grasslands plant diversity using satellite image time series is considered in this article. Fifteen months of freely available Sentinel optical and radar data were used to predict taxonomic and functional diversity at the pixel scale (10 m × 10 m) over a large geographical extent (40,000 km2). 415 field measurements were collected in 83 grasslands to train and validate several statistical learning methods. The objective was to link the satellite spectro-temporal data to the plant diversity indices. Among the several diversity indices tested, Simpson and Shannon indices were best predicted with a coefficient of determination around 0.4 using a Random Forest predictor and Sentinel-2 data. The use of Sentinel-1 data was not found to improve significantly the prediction accuracy. Using the Random Forest algorithm and the Sentinel-2 time series, the prediction of the Simpson index was performed. The resulting map highlights the intra-parcel variability and demonstrates the capacity of satellite image time series to monitor grasslands plant taxonomic diversity from an ecological viewpoint. Numéro de notice : A2020-004 Affiliation des auteurs : UPEM-LASTIG+Ext (2016-2019) Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1016/j.rse.2019.111536 Date de publication en ligne : 26/11/2019 En ligne : https://doi.org/10.1016/j.rse.2019.111536 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94296 [article]

Application of digital image processing in automated analysis of insect leaf mines / Yee Man Theodora Cho (2020)  

Permalink

A learning approach to evaluate the quality of 3D city models / Oussama Ennafii in Photogrammetric Engineering & Remote Sensing, PERS, vol 85 n° 12 (December 2019)    

Permalink

“Mapping-with”: The Politics of (Counter-)classification in OpenStreetMap / Clancy Wilmott in Cartographic perspectives, n° 92 (2019)  

Permalink

De l’origine des Pins de montagne européens / Renaud Cantegrel in Revue forestière française [en ligne], vol 71 n° 3 (2019)  

Permalink

Ensemble methods for pedestrian detection in dense crowds / Jennifer Vandoni (2019)  

Permalink

Scalable evaluation of 3D city models / Oussama Ennafii (2019)  

Permalink

Semantic aware quality evaluation of 3D building models : Modeling and simulation / Oussama Ennafii (2019)  

Permalink

The necessary yet complex evaluation of 3D city models: a semantic approach / Oussama Ennafii (2019)    

Permalink

A taxonomy of quality assessment methods for volunteered and crowdsourced geographic information / Lívia Castro Degrossi in Transactions in GIS, vol 22 n° 2 (April 2018)  

Permalink

Toward a working taxonomy of geodesign practice / David Tulloch in Transactions in GIS, vol 21 n° 4 (August 2017)  

Permalink