After we met with Dr. Clarke and Dr. Cobb, our two advisors for the project, we not only gained a better understanding of the project, but also of our scope over the next ten weeks. Currently, residents of Chatham county are relying on a singular gauge in Fort Pulaski for flooding predictions. Although this sensor is fairly accurate, the problem is that it’s only fairly accurate for that specific region. During hurricane Irma and Matthew, this gauge predicted that the magnitudes of the two storms would be roughly equal. However, the deployment of temporary sensors by the USGS showed that, for certain areas, Irma showed more severe flooding than Matthew. This difference was not captured by the Fort Pulaski gauge, thus the need for the current network of sea sensors. With a better understanding of the project motivations, our research question thus comes in two forms:
- Why is a sensor network necessary as opposed to the singular Fort Pulaski gauge?
- How do we justify the network’s permanence? What nuances and insights can we learn from it?
Communicating this information poses a challenge because there is a plethora of datasets to consider. Namely, how can we intuitively, but also meaningfully, incorporate space (geography) and time into our visualizations? What should we consider when building a visualization that should highlight the nuances of the geography?
We began the week by creating a storyboard of the motivations and desired outcomes of the project to organize our ideas. We then brainstormed ideas for possible visualizations that aim to communicate the importance of the sensor network. The primary tools we intend to use are two javascript libraries called D3 and Leaflet; D3 for visualizing the sensor data we have, and Leaflet for placing that data on the maps. We are all beginners in the world of data vis, but we’re having a ton of fun playing around with the features the libraries have to offer. After creating some initial visualization examples, we met with Dr. Ben Shapiro to get his feedback on our ideas. He answered our questions on how to best express time and spatial components of our data and helped us sketch further options for more complex visualizations. We plan to spend the rest of the week updating our models based on Dr. Shapiro’s feedback and to continue to build the first versions of our brainstormed ideas.