/green-spaces

This program models Neural Style Transfer and Pix2Pix to create a green spaces generation program

Primary LanguageJupyter Notebook

Green Space

Greener Urban Identity

The Lack of Green Space impacts daily living

  • Due to shifting economic and environment pressures on American cities, the amount of green spaces in cities is diminished when it is historically needed the most.
  • In the face of climate change, cities need to strategically design green spaces to lower temperatures, improve air quality, and mitigate flooding.

Utilizing of Imagery

  • Using multiple sataelite images of google earth, identify patches of green space to train the model in style transfer.
  • Specifically learning the color/shape/patterns of green spaces to then apply onto other map images that lack greenery.

Envisioning a Greener Urban Landscape

  • By generating greenery unto other cities that low green spaces density and/or high heat island effects. Approaches to AI would be through:
    • Style Transfer: Tests the style of greener images being placed into content images of urban images
    • Pix2Pix: Using manually applied colors on a map to achieve the appearance of more greenery