Volume XLII-4/W8
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 199–209, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-199-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-4/W8, 199–209, 2018
https://doi.org/10.5194/isprs-archives-XLII-4-W8-199-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  11 Jul 2018

11 Jul 2018

VISUALIZATION AND ANALYSIS OF CELLULAR & TWITTER DATA USING QGIS

B. Sowkhya1, S. Amaduzzi2, and D. Raawal1 B. Sowkhya et al.
  • 1CEPT University, Gujarat, India
  • 2Udine University, Udine, Italy

Keywords: QGIS, Twitter feed, Cellular data, Origin Destination Matrices, Thematic maps

Abstract. The study is to understand individual presence and movement in Friuli Venezia Giulia region. It is important for tourism planning, hazard management, business marketing, implementing government lifetime policies and benefit. The aim of this study is achieved by advanced web 2.0 applications. We need real time and geo-located data to monitor the inflow of tourist and to come up with effective promoting and benefiting plans for tourism, the evacuation and mitigation strategies during hazards to protect social life and environment with less infrastructure damage, marketing plans for advertising or selling of products. Despite wide spread success in predicting specific aspects of human behavior by social media information, a little attention is given to twitter and cell phone data. Accessibility to detailed human movements with fine spatial and temporal granularity is challenging due to confidentiality and safety reasons. With rapid development of web 2.0 applications people can post about events, share opinion and emotions online. Using twitter data, how short term travelers, such as tourists, can be recognized and how their travel pattern can be analyzed. Study of finding tourist dynamics such as arriving and outgoing of tourist, sum of trips, sum of days and night spent, number of unique visitors, country of residence, main destination, secondary destination, transits pass through, repeat visits are achieved using CDR (call detail records) and DDR (data detail records).