Meet The Team
Contact Information
- Matthew Britman (e) britmamp@dukes.jmu.edu
- Marina Wedlick (e) wedlicmi@dukes.jmu.edu
- Sofiya Gorban (e) gorbansx@dukes.jmu.edu
- Adam Rigsby (e) rigsbywa@dukes.jmu.edu
Introduction
The Megacities team (Sponsored by the NGA) is composed of 4 students with varying backgrounds. Sofiya, a junior, whose field of study is focused on general engineering with a minor in mathematics. Marina, a senior international affairs major, has a minor in Arabic; her work focuses mostly on Middle-Eastern based affairs. Adam, a senior political science major and public policy and administration minor, is on a pre-law track. Finally, Matthew is a senior international affairs major and political science minor, focusing on foreign policy and global governance. Together the team is concentrating on mapping informal settlements, and tracking their growth, within megacities. These cities are large population centers, with a total population of more than 10 million in the proper regions. Informal settlements are areas where housing develops on unauthorized land, or where housing is constructed that lack the necessary or required building permits, infrastructure, or regulations.
Our Problem
Currently, there isn't a way with which cities can track informal settlements that emerge within megacities when there are surges in population. The NGA is looking for a way in which these settlements may be mapped and tracked so that they may better inform decision makers when presenting data on informal settlements.
Week 13
During the week of November 9, our group made extensive progress as we were able to apply our knowledge to more physical ways of learning. We created an ARCGIS story map, detailing Jakarta’s informal settlements. As well, we furthered our research on the different levels of development within megacities, specifically informal settlements. There are three different components to development, all which are important to the dynamic as a whole.
Week 14
Throughout Week 14, the group came together to analyze and discuss the first official draft of our solution. After a lot of consideration we settled on the draft outlined in the presentation below. We were also able to get feedback from our professors on the execution of our solution and are now able to edit our final product to be a comprehensive solution for our stakeholder.
Week 15
This week the team presented our most comprehensive solution yet. All of our ideas came to fruition in a fully flushed presentation that is viewable in the link below. We received valuable feedback from professors and peers, enabling the team for our final presentation next week. At this stage, we have come to the conclusion that a supervised machine learning solution, using our 4 suggested variables, will enable the NGA and those whom they work with, to effectively, identify, track, and map informal settlements within megacities. At this point, our visual aid has also been completed and is linked below.
Above is an excerpt from our presentation, featuring a possible idea of what our machine learning process tree might look like.
Week 16
This week, the team worked on refining the final deliverables for our sponsor. Additionally, together we decided to come up with a better powerpoint, showcasing our ideas for a solution, as well as creating an executive summary for them to read with it. Analyzing feedback given to us by the instructors and collectively interpreted the information to improve the overall quality of our final presentation. Below we have linked our StoryMap, executive summary, and final presentation. Happy Holidays and Happy New Year!
Sources Used
Credits:
Created with images by sharonang - "beautiful amazing stunning" • iqbalnuril - "city jakarta indonesia" • stark8 - "xiamen slum dwellers street photography"