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Aim of this article, is to present a methodology for extracting macroseismic intensity information and producing seismic intensity maps from VGI (volunteered geographic information). As a VGI source for obtaining and assessing macroseismic observations, the authors chose twitter. Our methodology is validated in two recent earthquakes occurred in Greece: the January 26, 2014 ML = 5.8 in Kefallinia, and the November 17, 2014 ML = 5.2 in Evoikos. Twitter data published within the first 6 h, 12 h, 24 h and 48 h after the earthquake occurrence were analyzed to develop seismic intensity maps. Those maps were evaluated through intensity maps for the same earthquakes, published by international institutes. Evaluation results provide a strong empiric evidence for the credibility of our methodology, the accuracy of the produced seismic intensity maps and accentuate VGI, generated by twitter, as an adequate alternative source for collecting macroseismic information.

<p><strong>Abstract.</strong> 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&amp;thinsp;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&amp;thinsp;h, 12&amp;thinsp;h, 24&amp;thinsp;h, 48&amp;thinsp;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.</p>

The main purpose of this chapter is to introduce fundamental knowledge regarding the notion of volunteered geographic information (VGI) and its applications in disaster management (DM) of events related to floods. Initially, the meaning of the term is defined along with certain properties and general trends that characterize VGI. A brief literature review unfolds the range of activities that compose that certain term, along with its applications to flood event management. Those applications cover significant aspects of both VGI and DM cycle: from participatory activities of volunteers up to pure data analysis, extracted from social media and other VGI sources, while, in terms of DM cycle, from mitigation up to response and recovery. Finally, a set of four main clusters of open challenges is addressed. Those clusters accumulate the vast majority of open topics on this research field.

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