GreenUP

Input fields for the location and distance
Results- satellite image and data
Results- green grade and distance map
Homepage of our website

Inspiration

There is no single application that can estimate green space given coordinates or a location. We drew inspiration from the necessity of green space in sustainable urban planning, and on further research, came up with a novel idea to raise awareness about green spaces in cities.

What it does

GreenUP utilizes satellite images to determine the amount of 'green' in a particular area defined by two user inputs - location and distance. After determining the amount of green area, a 'green grade' is assigned. This letter grade reflects the sufficiency of green space.

How we built it

GreenUP was built entirely using the Wolfram Language.

Challenges we ran into

• Most maps are entirely green. We solved this by taking a range of green shades. • Coming up with the most suitable map resolution to work with. • In several maps, greenish water bodies are incorrectly calculated as green space. This requires more time to refine.

Accomplishments that we're proud of

• We were able to get near-accurate values for heavily industrialized cities vs suburban locations. • In several cities such as Chicago, GreenUP successfully ignored water bodies as green space. • We did all of this in 48 hours!

What we learned

• Many cities lack sufficient green space for human health and sustainability.

What's next for GreenUP

• Refine our algorithm by also identifying polygons and larger green spaces. • Attempt to classify them as private or public green spaces. • Modify our letter-grading system such that it is not solely dependent on the ratio of green area to total area, but also takes in factors like size, distance from the user, and the quality of green space into account.