Volume XLII-3/W4
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 59-66, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-59-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci., XLII-3/W4, 59-66, 2018
https://doi.org/10.5194/isprs-archives-XLII-3-W4-59-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.

  06 Mar 2018

06 Mar 2018

DEVELOPING SEISMIC INTENSITY MAPS FROM TWITTER DATA; THE CASE STUDY OF LESVOS, GREECE 2017 EARTHQUAKE: ASSESSMENTS, IMPROVEMENTS AND ENRICHMENTS ON THE METHODOLOGY

S. G. Arapostathis1, E. Lekkas2, K. Kalabokidis3, G. Xanthopoulos5, G. Drakatos4, N. Spirou2, and I. Kalogeras4 S. G. Arapostathis et al.
  • 1Department of Geography, Harokopio University, Athens, Greece
  • 2Department of Geology, University of Athens, Athens, Greece
  • 3Department of Geography, University of the Aegean, Mytilene, Greece
  • 4Institute of Geodynamics of the National Observatory of Athens, Greece
  • 5Institute of Mediterranean Forest Ecosystems and Forest Products Technology, Athens, Greece

Keywords: seismic intensity, twitter, volunteered geographic information, VGI

Abstract. This article presents an effort to validate and further improve a previously published innovative approach for drawing macroseismic intensity maps from data extracted from sources of volunteered geographic information (VGI). Our approach involves classification of macroseismic observations (extracted from social media sources) to values of the EMS 98 intensity scale, leading to the drawing of isoseismal maps. The earthquake of June 12th, 2017 (Mw 6.3) that occurred off the south coast of Lesvos Island, Greece, was used as a case study; its main shock was located at depth of about 13 km. This specific event, which claimed the life of a woman and caused at least 15 injuries due to collapsing buildings and falling debris (mainly in the town of Vrissa), was chosen for the specific geomorphological characteristics of the meizoseismal area, time of occurrence and distribution of damage. Twitter was chosen as a VGI source mostly for reasons of consistency with the original published work, generating comparable findings that can be assessed more readily to facilitate further development of the methodology. Results of the dataset analysis include the drawing of the isoseismal maps from Tweets published within different time periods (6 h, 12 h, 24 h, 48 h); and the identification of various text patterns regarding the evaluation of the macroseismic observations that result into intensity values. The present work offers additional empirical evidence regarding the validity of the methodology presented in the scientific literature, and further enriches it by providing additional text patterns and specific improvements related to the classification of the information in certain values of seismic intensity. Assessment of the results is enriched by the progress that has been noted in the field and has been presented in the international scientific literature since 2016.