Alex Moltzau 莫战

Mar 15, 2020

4 min read
Photo by @felixrstg

Urban Canopy Cover with AI

Understanding the Green in Cities Better with Artificial Intelligence

Looking across a city it is a great different whether you see green splashes, dots or just grey. Both to mitigate the impact of climate change in cities, yet also for wellbeing. Urban canopy cover can help mitigating the impact of increasing daytime summer temperatures. Reading up on the Climate Change AI workshop held at NeurIPS 2019 there was a paper called that I wanted to read.

Urban Tree Canopy (UTC) refers to the layer of tree leaves, branches, and stems that provide tree coverage of the ground when viewed from above.

An example of existing ways to measure this is usually with a degree of segmentation and satellite images (or data from areas). It could look something like this:

Percent tree canopy cover within California urban areas. CREDIT University of California, Davis

Or this:

Physical models show that urban trees can significantly reduce the diurnal temperature range.

In meteorology, diurnal temperature variation is the variation between a high temperature and a low temperature that occurs during the same day.

So there you have it, a short explanation of some benefits, however what does the paper in question say?

Urban Canopy Cover with AI

The abstract of the paper reads as follow.

As mentioned above tree canopy has a lot of benefits.

Their argument is that it can reduce peak temperatures on the hot days.

Other benefits they mention in the introduction is:

  • Removal of air pollution.
  • Increased perceived neighbourhood safety.
  • Better visual and aesthetic appeal for residents.

The writers of the research paper argues that current methods to measure canopy cover is inadequate.

Traditional vs. New

They contrast traditional measurement.

Traditional methods: rely on either overhead imagery or in-person fieldwork.

As opposed to their method that takes images on-the-ground.

In simple English: they find the trees, bushes, etc.

I found an interesting visualisation in their appendix too representing Boston and London.

Combine?

I thought it was interesting to think about the potential of combining these different datasets for moderation to get a clearer picture of whether it is true or perhaps finding a way to more accurately map how green a city is. Each method has its limitations, but together and combined it may create a realisation of the true representation of the vegetation.