Results

The goal of our map was to highlight several factors and key statistics that determine if a certain zip code within Miami-Dade County is feasible for solar panels. As a team, the solution decided was to use an interactive map called MapHub as it gave us better accessibility to be able to construct our map. It also allowed us to reference the "design process" page on our portfolio, so even if a user is unaware of what our methodology was, they can read it for themselves to get a better understanding of what we did and why we did it.

Some of the key points of our project include:

• The data displayed include data such as average elevation and flood risk ranging from minimal to extreme.

• The data relevant to solar panel investment was extracted from Google Project Sunroof such as average roof space, annual electricity generated per building, and annual cost savings.

• The map demonstrates each zip code with a highlighted color which is meant to show if solar panels are recommended in the area or not.

The colors are red, yellow, and green; red is for areas that are not recommended for solar panel construction after gathering extensive data. Yellow is for areas that show minimal concern correlating to flood risks and elevation but solar panels are still recommended for those respective locations. Lastly, green is for optimal locations that are best suited for the implementation of solar panels. The map will help decision-makers and government officials in Miami-Dade County as a guide to tackle climate issues and implement renewable energy sources.

View The Interactive Map By Clicking Here!

Future Work

For future shifts and implementations, we will maintain in touch with our stakeholders, local news, advisors, and information regarding the innovation of resources and advances in technology. Since more tools are gradually being implemented and considering they might be capable of performing tasks faster and providing more feasible solutions for Miami-Dade locals, our team must ensure that we will be adapting to them properly.

We sincerely believe this can be a framework for future work, which could be international and account for the most threatening hazards in different parts of the world, yielding a more resilient global energy grid. With more resources and a stronger background in the software design, it could be automated to update the values present in the map, as well as adjust the recommendations based on the decision matrix the system is based on.