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Evaluating geo-tagged Twitter data to analyze tourist flows in Styria, Austria / Johannes Scholz in ISPRS International journal of geo-information, vol 9 n° 11 (November 2020)  

Public [article]  inISPRS International journal of geo-information > vol 9 n° 11 (November 2020) . - n° 681 Titre : Evaluating geo-tagged Twitter data to analyze tourist flows in Styria, Austria Type de document : Article/Communication Auteurs : Johannes Scholz, Auteur ; Janja Jeznik, Auteur Année de publication : 2020 Article en page(s) : n° 681 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Analyse spatiale [Termes IGN] Autriche [Termes IGN] coefficient de corrélation [Termes IGN] contenu généré par les utilisateurs [Termes IGN] distribution spatiale [Termes IGN] méthode fondée sur le noyau [Termes IGN] segmentation sémantique [Termes IGN] tourisme [Termes IGN] Twitter Résumé : (auteur) The research focuses on detecting tourist flows in the Province of Styria in Austria based on crowdsourced data. Twitter data were collected in the time range from 2008 until August 2018. Extracted tweets were submitted to an extensive filtering process within non-relational database MongoDB. Hotspot Analysis and Kernel Density Estimation methods were applied, to investigate spatial distribution of tourism relevant tweets under temporal variations. Furthermore, employing the VADER method an integrated semantic analysis provides sentiments of extracted tweets. Spatial analyses showed that detected Hotspots correspond to typical Styrian touristic areas. Apart from mainly successful sentiment analysis, it pointed out also a problematic aspect of working with multilingual data. For evaluation purposes, the official tourism data from the Province of Styria and federal Statistical Office of Austria played a role of ground truth data. An evaluation with Pearson’s correlation coefficient was employed, which proves a statistically significant correlation between Twitter data and reference data. In particular, the paper shows that crowdsourced data on a regional level can serve as accurate indicator for the behaviour and movement of users. Numéro de notice : A2020-731 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE Nature : Article nature-HAL : ArtAvecCL-RevueIntern DOI : 10.3390/ijgi9110681 Date de publication en ligne : 15/11/2020 En ligne : https://doi.org/10.3390/ijgi9110681 Format de la ressource électronique : url article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=96344 [article]

Modelling a dynamic forest fuelmarket focusing on wood chips: a spatial agent-based approach to simulate competition among heating plants in the province of Carinthia, Austria / Johannes Scholz in GI Forum, vol 2017 n° 1 ([01/01/2017])  

Public [article]  inGI Forum > vol 2017 n° 1 [01/01/2017] . - pp 383 - 396 Titre : Modelling a dynamic forest fuelmarket focusing on wood chips: a spatial agent-based approach to simulate competition among heating plants in the province of Carinthia, Austria Type de document : Article/Communication Auteurs : Johannes Scholz, Auteur ; Florian Breitwieser, Auteur ; Peter Mandl, Auteur Année de publication : 2017 Article en page(s) : pp 383 - 396 Note générale : bibliographie Langues : Anglais (eng) Descripteur : [Vedettes matières IGN] Applications SIG [Termes IGN] agent (intelligence artificielle) [Termes IGN] Autriche [Termes IGN] biomasse (combustible) [Termes IGN] marché du bois [Termes IGN] modèle orienté agent [Termes IGN] modélisation spatio-temporelle [Termes IGN] simulation dynamique Résumé : (auteur) Sustainability and renewable resources are attracting increased attention in the energy supply sector. This paper elaborates on the application of agent-based modelling methods to simulate forest fuel markets and supply chains. More precisely, it aims to simulate the market for wood chips for heating purposes, based on a sustainable forest growth and yield model, in conjunction with cognitive agents that act in the market. In the agent-based model, three types of agents are defined: forest owners (supply), biomass heating plant (demand), and ‘traders’, connecting supply and demand. Forest enterprises can decide on forest operations based on the state of the forest fuel market – e.g. considering the price for wood chips. Each biomass heating plant has an associated ‘trader’ that tries to fulfil the demand for forest biomass while minimizing the transport distances and the cost for the wood chips. The paper discusses the results of a simulation scenario in the Province of Carinthia, Austria. The simulation results are analysed with respect to space and time concerning biomass transport distance, transport patterns and remaining biomass stock. Numéro de notice : A2017-872 Affiliation des auteurs : non IGN Thématique : FORET/GEOMATIQUE Nature : Article DOI : 10.1553/giscience2017_01_s383 Date de publication en ligne : 30/06/2017 En ligne : https://doi.org/10.1553/giscience2017_01_s383 Format de la ressource électronique : URL article Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=90393 [article]