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Utilizing Geo-Social Media as a Proxy Data for Enhanced Flood Monitoring

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Abstract

Social media plays an important role in disseminating spontaneous information during natural disasters/emergencies. It is a crowdsourcing platform, capable of complementing and supplementing remote sensing data in disaster mapping. Continuous monitoring of disasters such as floods from pre-stage to post stage is essential and geo-social media can attain it. The present research proposes a robust architecture to develop a social media-based near-real time flood monitoring system. In addition, our research article also emphasizes the efficient methods to process, analyse and explore multiple data dimensions of social media. A prototype model was prepared and tested on the tweets of Chennai floods 2015 to demonstrate social media potential in disaster monitoring. We implemented Natural Language Processing and Supervised Machine Learning in data processing and analysis segments of the framework by assembling various open source python libraries to develop the prototype. Initially, we built the required tweet corpus and performed pre-processing steps on it. Later, the collected tweets were geocoded with the place names available in the tweets and classified them into various flood topic related classes using Naive Bayes classifier. Subsequently, the tweets showcasing the flood condition were determined to generate a point map and a point density map to identify the flood hotspots. We verified our results with openly available 2015 Chennai flood map that is generated using remote sensing images and found positive outcome. A prototype web portal was developed to publish the results from above model as web maps. Furthermore, the portal would prove to be useful as a source for disseminating information to the public. The results prove that the proposed framework is evidently supportive in establishing a near real time monitoring system during emergencies.

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Authors and Affiliations

  1. Geoinformatics Division, Centre for Space Science and Technology Education in Asia and The Pacific (CSSTEAP), Dehradun, India

    Jaya Surya Sattaru

  2. Disaster Management Sciences, Indian Institute of Remote Sensing, Dehradun, India

    C. M. Bhatt

  3. Geoinformatics Division, Indian Institute of Remote Sensing, Dehradun, India

    Sameer Saran

Authors
  1. Jaya Surya Sattaru
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  2. C. M. Bhatt
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  3. Sameer Saran
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Correspondence to Jaya Surya Sattaru.

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Sattaru, J.S., Bhatt, C.M. & Saran, S. Utilizing Geo-Social Media as a Proxy Data for Enhanced Flood Monitoring. J Indian Soc Remote Sens 49, 2173–2186 (2021). https://doi.org/10.1007/s12524-021-01376-9

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  • DOI: https://doi.org/10.1007/s12524-021-01376-9

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