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Puerto Rico is exposed to multiple hazards including hurricanes, earthquakes, and floods. The Resilient Infrastructure and Sustainability Education Undergraduate Program (RISE-UP) at the University of Puerto Rico aims to introduce students to interdisciplinary problem-solving related to real challenges, especially those associated with the occurrence of natural disasters. The objective of this work is to share our experience with experiential learning related to structural engineering. The lessons learned from this experience, from the student ́s perspective, could encourage faculty members to develop similar undertakings in their programs and students to participate when opportunities arise. During the 2019 fall semester, we enrolled in a course which covered the relationship between design and natural disasters, with an emphasis on rapid response to recover during the aftermath. The course combined lectures and in-class exercises on basic structural analysis, classifications of structures and the use of the FEMA Rapid Visual Screening (P-154) form. This was complemented with field visits of structures affected by Hurricane Maria where we developed several case studies. From December of 2019 to February 2020, Puerto Rico suffered an earthquake swarm reaching magnitudes as high as 6.4, which caused structural damages throughout the South West of the island. Following these events, we were able to use the training acquired during our course in a real-life, post-disaster situation. At the University, we participated in visual inspection brigades, where we aided professional engineers and faculty members in data collection and categorizing building damages. Our involvement helped streamline efforts as we provided additional support in report writing and organization of the data collected using GIS and other tools. The results of the visual inspections indicated that in many cases pre- existing conditions were aggravated by the earthquakes. Furthermore, we also witnessed firsthand the complexities of assessing infrastructure damage during and following high seismic activity. This experience enhanced our awareness of the significance of our profession in ensuring the safety of others both immediately after an earthquake and in the face of future disasters.
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A comparison of people’s use of Twitter in Puerto Rico Earthquake and Hurricane Maria
The purpose of the Twitter Disaster Behavior project is to identify patterns in online behavior during natural disasters by analyzing Twitter data. The main goal is to better understand the needs of a community during and after a disaster, to aid in recovery. The datasets analyzed were collections of tweets about Hurricane Maria, and recent earthquake events, in Puerto Rico. All tweets pertaining to Hurricane Maria are from the timeframe of September 15 through October 14, 2017. Similarly, tweets pertaining to the Puerto Rico earthquake from January 7 through February 6, 2020 were collected. These tweets were then analyzed for their content, number of retweets, and the geotag associated with the author of the tweet. We counted the occurrence of key words in topics relating to preparation, response, impact, and recovery. This data was then graphed using Python and Matplotlib. Additionally, using a Twitter crawler, we extracted a large dataset of tweets by users that used geotags. These geotags are used to examine location changes among the users before, during, and after each natural disaster. Finally, after performing these analyses, we developed easy to understand visuals and compiled these figures into a poster. Using these figures and graphs, we compared the two datasets in order to identify any significant differences in behavior and response. The main differences we noticed stemmed from two key reasons: hurricanes can be predicted whereas earthquakes cannot, and hurricanes are usually an isolated event whereas earthquakes are followed by aftershocks. Thus, the Hurricane Maria dataset experienced the highest amount of tweet activity at the beginning of the event and the Puerto Rico earthquake dataset experienced peaks in tweet activity throughout the entire period, usually corresponding to aftershock occurrences. We studied these differences, as well as other important trends we identified.
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- PAR ID:
- 10210433
- Date Published:
- Journal Name:
- International Conference on Information Systems for Crisis Response and Management
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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