Descripteur
Termes IGN > sciences humaines et sociales > économie > macroéconomie
macroéconomieVoir aussi |
Documents disponibles dans cette catégorie (1763)
Ajouter le résultat dans votre panier
Visionner les documents numériques
Affiner la recherche Interroger des sources externes
Etendre la recherche sur niveau(x) vers le bas
Geological map generalization driven by size constraints / Azimjon Sayidov in ISPRS International journal of geo-information, vol 9 n° 4 (April 2020)
[article]
Titre : Geological map generalization driven by size constraints Type de document : Article/Communication Auteurs : Azimjon Sayidov, Auteur ; Meysam Aliakbarian, Auteur ; Robert Weibel, Auteur Année de publication : 2020 Article en page(s) : 29 p. Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation
[Termes IGN] carte géologique
[Termes IGN] données environnementales
[Termes IGN] généralisation automatique de données
[Termes IGN] opérateur de généralisation
[Termes IGN] programmation par contraintes
[Termes IGN] prospection minérale
[Termes IGN] taille (variable visuelle)
[Vedettes matières IGN] GénéralisationRésumé : (auteur) Geological maps are an important information source used in the support of activities relating to mining, earth resources, hazards, and environmental studies. Owing to the complexity of this particular map type, the process of geological map generalization has not been comprehensively addressed, and thus a complete automated system for geological map generalization is not yet available. In particular, while in other areas of map generalization constraint-based techniques have become the prevailing approach in the past two decades, generalization methods for geological maps have rarely adopted this approach. This paper seeks to fill this gap by presenting a methodology for the automation of geological map generalization that builds on size constraints (i.e., constraints that deal with the minimum area and distance relations in individual or pairs of map features). The methodology starts by modeling relevant size constraints and then uses a workflow consisting of generalization operators that respond to violations of size constraints (elimination/selection, enlargement, aggregation, and displacement) as well as algorithms to implement these operators. We show that the automation of geological map generalization is possible using constraint-based modeling, leading to improved process control compared to current approaches. However, we also show the limitations of an approach that is solely based on size constraints and identify extensions for a more complete workflow. Numéro de notice : A2020-261 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9040284 Date de publication en ligne : 24/04/2020 En ligne : https://doi.org/10.3390/ijgi9040284 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=95021
in ISPRS International journal of geo-information > vol 9 n° 4 (April 2020) . - 29 p.[article]Street-Frontage-Net: urban image classification using deep convolutional neural networks / Stephen Law in International journal of geographical information science IJGIS, vol 34 n° 4 (April 2020)
[article]
Titre : Street-Frontage-Net: urban image classification using deep convolutional neural networks Type de document : Article/Communication Auteurs : Stephen Law, Auteur ; Chanuki Illushka Seresinhe, Auteur ; Yao Shen, Auteur Année de publication : 2020 Article en page(s) : pp 681- 707 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] apprentissage profond
[Termes IGN] classification par réseau neuronal convolutif
[Termes IGN] espace public
[Termes IGN] évaluation foncière
[Termes IGN] extraction de données
[Termes IGN] façade
[Termes IGN] habitat urbain
[Termes IGN] image Streetview
[Termes IGN] immobilier (secteur)
[Termes IGN] information géographique
[Termes IGN] Londres
[Termes IGN] matrice de confusion
[Termes IGN] Paris (75)
[Termes IGN] paysage urbain
[Termes IGN] urbanisme
[Termes IGN] vision par ordinateurRésumé : (auteur) Quantifying aspects of urban design on a massive scale is crucial to help develop a deeper understanding of urban designs elements that contribute to the success of a public space. In this study, we further develop the Street-Frontage-Net (SFN), a convolutional neural network (CNN) that can successfully evaluate the quality of street frontage as either being active (frontage containing windows and doors) or blank (frontage containing walls, fences and garages). Small-scale studies have indicated that the more active the frontage, the livelier and safer a street feels. However, collecting the city-level data necessary to evaluate street frontage quality is costly. The SFN model uses a deep CNN to classify the frontage of a street. This study expands on the previous research via five experiments. We find robust results in classifying frontage quality for an out-of-sample test set that achieves an accuracy of up to 92.0%. We also find active frontages in a neighbourhood has a significant link with increased house prices. Lastly, we find that active frontage is associated with more scenicness compared to blank frontage. While further research is needed, the results indicate the great potential for using deep learning methods in geographic information extraction and urban design. Numéro de notice : A2020-110 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/13658816.2018.1555832 Date de publication en ligne : 26/12/2018 En ligne : https://doi.org/10.1080/13658816.2018.1555832 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94712
in International journal of geographical information science IJGIS > vol 34 n° 4 (April 2020) . - pp 681- 707[article]Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi / Brad G. Peter in Photogrammetric Engineering & Remote Sensing, PERS, vol 86 n° 2 (February 2020)
[article]
Titre : Multi-Spatial Resolution Satellite and sUAS Imagery for Precision Agriculture on Smallholder Farms in Malawi Type de document : Article/Communication Auteurs : Brad G. Peter, Auteur ; Joseph P. Messina, Auteur ; Jon W. Carroll, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 107 - 119 Note générale : Bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Traitement d'image optique
[Termes IGN] agriculture de précision
[Termes IGN] analyse multirésolution
[Termes IGN] exploitation agricole
[Termes IGN] image Pléiades
[Termes IGN] image Sentinel-MSI
[Termes IGN] image SPOT 6
[Termes IGN] MalawiRésumé : (Auteur) A collection of spectral indices, derived from a range of remote sensing imagery spatial resolutions, are compared to on-farm measurements of maize chlorophyll content and yield at two trial farms in central Malawi to evaluate what spatial resolutions are most effective for relating multispectral images with crop status. Single and multiple linear regressions were tested for spatial resolutions ranging from 7 cm to 20 m using a small unmanned aerial system (sUAS) and satellite imagery from Planet, SPOT 6, Pléiades, and Sentinel-2. Results suggest that imagery with spatial resolutions nearer the maize plant scale (i.e., 14–27 cm) are most effective for relating spectral signals with crop health on smallholder farms in Malawi. Consistent with other studies, green-band indices were more strongly correlated with maize chlorophyll content and yield than conventional red-band indices, and multivariable models often outperformed single variable models. Numéro de notice : A2020-127 Affiliation des auteurs : non IGN Thématique : IMAGERIE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.14358/PERS.86.2.107 Date de publication en ligne : 01/02/2020 En ligne : https://doi.org/10.14358/PERS.86.2.107 Format de la ressource électronique : URL Article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94796
in Photogrammetric Engineering & Remote Sensing, PERS > vol 86 n° 2 (February 2020) . - pp 107 - 119[article]Semantic relatedness algorithm for keyword sets of geographic metadata / Zugang Chen in Cartography and Geographic Information Science, vol 47 n° 2 (February 2020)
[article]
Titre : Semantic relatedness algorithm for keyword sets of geographic metadata Type de document : Article/Communication Auteurs : Zugang Chen, Auteur ; Yaping Yang, Auteur Année de publication : 2020 Article en page(s) : pp 125 - 140 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Géomatique web
[Termes IGN] descripteur
[Termes IGN] Infrastructure de données
[Termes IGN] internet interactif
[Termes IGN] métadonnées géographiques
[Termes IGN] relation sémantique
[Termes IGN] similitude sémantique
[Termes IGN] système à base de connaissances
[Termes IGN] terminologie
[Termes IGN] thesaurusRésumé : (auteur) Advances in linked geospatial data, recommender systems, and geographic information retrieval have led to urgent necessity to assess the overall semantic relatedness between keyword sets of geographic metadata. In this study, a new model is proposed for computing the semantic relatedness between arbitrary two keyword sets of geographic metadata stored in current global spatial data infrastructures. In this model, the overall semantic relatedness is derived by pairing these keywords that are found to be most relevant to each other and averaging their relatedness. To find the most relevant keywords across two keyword sets precisely, the keywords in the keyword set of geographic metadata are divided into three kinds: the thesaurus elements, the WordNet elements, and the statistical elements. The thesaurus-lexical relatedness measure (TLRM), the extended thesaurus-lexical relatedness measure (ETLRM), and the Longest Common Substring method are proposed to compute the semantic relatedness between two thesaurus elements, two WordNet elements, a thesaurus element, and a WordNet element and two statistical elements, respectively. A human data set – the geographic-metadata’s keyword set relatedness dataset, which was used to evaluate the precision of the semantic relatedness measures of keyword sets of geographic metadata, was created. The proposed method was evaluated against the human-generated relatedness judgments and was compared with the Jaccard method and Vector Space Model. The results demonstrated that the proposed method achieved a high correlation with human judgments and outperformed the existing methods. Finally, the proposed method was applied to quantitatively linked geospatial data. Numéro de notice : A2020-057 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.1080/15230406.2019.1647797 Date de publication en ligne : 20/09/2017 En ligne : https://doi.org/10.1080/15230406.2019.1647797 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=94573
in Cartography and Geographic Information Science > vol 47 n° 2 (February 2020) . - pp 125 - 140[article]Spatial visualization of quantitative landscape changes in an industrial region between 1827 and 1883. Case study Katowice, southern Poland / Paweł Cybulski in Journal of maps, vol 16 n° 1 ([02/01/2020])
[article]
Titre : Spatial visualization of quantitative landscape changes in an industrial region between 1827 and 1883. Case study Katowice, southern Poland Type de document : Article/Communication Auteurs : Paweł Cybulski, Auteur ; Lukasz Wielebski, Auteur ; Beata Medyńska-Gulij, Auteur ; et al., Auteur Année de publication : 2020 Article en page(s) : pp 77 - 85 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG
[Termes IGN] 1:100.000
[Termes IGN] analyse spatio-temporelle
[Termes IGN] carte thématique
[Termes IGN] dégradation de l'environnement
[Termes IGN] détection de changement
[Termes IGN] dix-neuvième siècle
[Termes IGN] géoréférencement
[Termes IGN] paysage industriel
[Termes IGN] Pologne
[Termes IGN] prospection minérale
[Termes IGN] système d'information géographique
[Termes IGN] visualisation cartographiqueRésumé : (auteur) The aim of the study is to present landscape changes in the nineteenth century in the central part of the Upper Silesian Industrial District, which is the municipality of Katowice (southern Poland). The comparison of changes, particularly components of the geographical environment, is based on two time periods – the year 1827 and 1883. Nineteenth-century maps were georeferenced, digitized and a series of thematic spatial visualizations presenting quantitative changes were generated by means of the Geographic Information System (GIS). The scale of the visualization created is 1:100,000 and the area is 16,400 ha. The spatial visualization of quantitative landscape change shows the development of the anthropogenic pressure in the form of settlement areas, raw materials extraction places, roads, and the decrease of natural environments, such as forests, rivers, and water bodies. These changes were caused mainly by the exploration of underground deposits and the rapidly growing population of Upper Silesia. Numéro de notice : A2020-643 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article DOI : 10.1080/17445647.2020.1746416 Date de publication en ligne : 04/04/2020 En ligne : https://doi.org/10.1080/17445647.2020.1746416 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96069
in Journal of maps > vol 16 n° 1 [02/01/2020] . - pp 77 - 85[article]Analyse, structuration et sémantisation des images aériennes [diaporama] / Valérie Gouet-Brunet (2020)PermalinkCartographie sémantique hybride de scènes urbaines à partir de données image et Lidar / Mohamed Boussaha (2020)PermalinkCreating a web mapping portal to manage Malta’s underwater cultural heritage / Mélissa Dupuis (2020)PermalinkCréation d’un outil d’interrogation du référentiel régional pédologique de Bretagne pour estimation du stock de carbone organique du sol / Louise Grall (2020)PermalinkPermalinkImproved indoor positioning based on range-free RSSI fingerprint method / Marcin Uradzinski in Journal of geodetic science, vol 10 n° 1 (January 2020)PermalinkIndividual internet usage and the availability of online content of local interest: A multilevel approach / Emmanouil Tranos in Computers, Environment and Urban Systems, vol 79 (January 2020)PermalinkPermalinkOptimisation des services de positionnement GNSS pour les opérations offshore d’Exploration Production de Total / Gautier Jolain (2020)PermalinkPermalinkPermalinkPermalinkPermalinkPermalinkSUMAC'20 : Proceedings of the 2nd Workshop on Structuring and Understanding of Multimedia heritAge Contents / Valérie Gouet-Brunet (2020)PermalinkMeasuring differential access to facilities between population groups using spatial Lorenz curves and related indices / Gordon A. Cromley in Transactions in GIS, Vol 23 n° 6 (November 2019)PermalinkMapping the wavelength position of mineral features in hyperspectral thermal infrared data / Christoph Hecker in International journal of applied Earth observation and geoinformation, vol 79 (July 2019)PermalinkAudiovisual cartography : Established and new multimedia approaches to represent soundscapes / Dennis Edler in KN, Journal of Cartography and Geographic Information, vol 69 n° 1 (May 2019)PermalinkDévelopper l’Afrique, grâce au recensement des stations GNSS permanentes / Derrick Koome in XYZ, n° 158 (mars 2019)PermalinkLe nivellement de Saint-Germain-en-Laye / Alain Coulomb in XYZ, n° 158 (mars 2019)Permalink