Gis &amp; Visual Analytics on Grid Technology

Bonazountas, Marc; Kanellopoulos, S.A.; Schaller, Joerg; Kallidromitou, Despina; Martirano, Giacomo

doi:10.1007/978-90-481-2899-0_22

Cited by 2 publications

(2 citation statements)

References 3 publications

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“…For example, GIS has been used to identify the causes of natural or man-made disasters by analyzing the geographic properties of these events, to improve future prediction and preventive measures [32,33]. Likewise, for tourism site development [34] and city transportation system planning [35,36], research has taken advantage of analyzing information on geographic properties to identify the reason or evolution pattern of an object or event and thus to reveal its influential factors or diving mechanism and make predictions, interventions and prevention strategies by referring to its temporal and spatial evolution [37][38][39].…”

Section: Literature Reviewmentioning

confidence: 99%

The Temporal and Spatial Evolution of Marathons in China from 2010 to 2018

Zuo

Zou

Zhang

et al. 2019

IJERPH

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The purpose of this study is to explore the spatial distribution pattern and influencing factors of the Chinese marathon. Geographic Information System (GIS) related spatial analysis tools were used to calculate the following-averaged nearest neighbor index, nuclear density analysis and hot spot analysis among others. The spatial distribution evolution characteristics and the influencing factors of eighteen Chinese marathon events in 2010, 129 in 2015 and 342 in 2018 were analyzed. The results show that (a) in 2010 the nearest neighbor ratio was 1.164714, Moran's I was −0.010165 (type: Random), in 2015 it was 0.502146, Moran's I was 0.066267 (type: Clustered) and in 2018 it was 0.531149 and Moran's I was 0.083485 (type: Clustered); (b) in 2010 there was a 333.6 km search radius; the core circle of the Yangtze River Delta was adopted. In 2015 and 2018, a search radius of 556 km was adopted, which was respectively obtained from the core circle of the Yangtze River Delta, the core circle of Beijing-Tianjin-Hebei and the core circle of East China; (c) according to the Z-value data, East China and North China in 2015 passed 95% confidence in five provinces and municipal hot spots, passed 90% confidence in three hot spots and passed 95% confidence in Chongqing Cold Point. In 2018, East China, North China, Central Region and eight other provinces and cities' hot spots passed 95% confidence, four hot spots passed 90% confidence, the Tibet Autonomous Region cold spot passed 90% confidence. Conclusion: The overall distribution of marathon events is greater in the eastern region than the western region, greater in the southern region than the northern region and greater in coastal regions than the inland regions; the nuclear density distribution has spread from the Yangtze River Delta mononuclear circle in 2010 to the core circle of the entire East China region. Moreover, it spread to North China, Central China and South China; the distribution of hot spots spread from Shanghai, Jiangsu and Zhejiang to the entire North China and East China regions. During the past thirty-eight years of development of the Chinese marathon, it has been divided into three stages due to different political, economic and social environments.

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Section: Literature Reviewmentioning

confidence: 99%

The Temporal and Spatial Evolution of Marathons in China from 2010 to 2018

Zuo

Zou

Zhang

et al. 2019

IJERPH

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“…Visual analytics has been applied in decision making systems to support a wide range of application fields and decision tasks. Visual analytics have been applied in geospatial information to support for spatial decision support, a field called GeoVisual Analytics (GVA) in numerous studies [235,236,237,238,246], from simulations models that use Geographic and Meteorological Information to visualize natural phenomena, such as environmental hazards, in real time [237], to crisis management for emergency support [246]. Moreover, visual analytics has also supported decision making on economic [243, 244,247] and health care sector [245,249], as well as on environmental [251] and maritime decision making [248].…”

Section: Literature Review On the Combination Of Decision Making And ...mentioning

confidence: 99%

Visual interactive knowledge management for multicriteria decision making and ranking in linked open data environments

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Η διδακτορική διατριβή αφορά στην εφαρμογή της οπτικής αναλυτικής και των τεχνολογιών σημασιολογικού ιστού στην πολυκριτηριακή λήψη αποφάσεων και πιο συγκεκριμένα σε προβλήματα κατάταξης εναλλακτικών, στο πλαίσιο των ερευνητικών και ακαδημαϊκών πληροφοριακών συστημάτων. Οι οπτικοποιήσεις υποστηρίζονται επίσης από διαδικασίες εξόρυξης δεδομένων και εξαγωγής γνώσης σε περιβάλλοντα διασυνδεδεμένων δεδομένων. Επιπροσθέτως, θα χρησιμοποιηθούν τεχνικές οπτικής αναλυτικής για την οργάνωση των οπτικοποιήσεων, προκειμένου να παρουσιαστούν οι πληροφορίες με τέτοιο τρόπο που θα αξιοποιηθούν οι αντιληπτικές ικανότητες των χρηστών και τελικά θα ενισχύσουν τις διαδικασίες υποστήριξης αποφάσεων και χάραξης πολιτικής. Επιπλέον, η οπτική αναπαράσταση και κατά συνέπεια οι διαδικασίες λήψης αποφάσεων και χάραξης πολιτικής θα βελτιωθούν μέσω των σημασιολογικών τεχνολογιών που βασίζονται σε εννοιολογικά μοντέλα με τη μορφή οντολογιών. Έτσι, ο κύριος στόχος της παρούσας διδακτορικής διατριβής είναι ο συνδυασμός των σημασιολογικών τεχνολογιών με τεχνικές διαδραστικών οπτικοποιήσεων, προκειμένου να γίνουν πιο αποτελεσματικά τα συστήματα υποστήριξης αποφάσεων. Κατά την διάρκεια του διδακτορικού αναπτύχθηκε ένα πολυδιάστατο πλαίσιο βασισμένο σε οντολογίες για οπτική κατάταξη (MOBVR framework), το οποίο το εφαρμόστηκε σε δυο μελέτες περίπτωσης, η πρώτη ήταν ο ακαδημαϊκός τομέας και η δεύτερη ήταν οι δείκτες παγκόσμιας ανάπτυξης.

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Gis & Visual Analytics on Grid Technology

Cited by 2 publications

References 3 publications

The Temporal and Spatial Evolution of Marathons in China from 2010 to 2018

The Temporal and Spatial Evolution of Marathons in China from 2010 to 2018

Visual interactive knowledge management for multicriteria decision making and ranking in linked open data environments

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