# Studying oppressive cityscapes of Bangladesh

## TL;DR

This paper uses computer vision to analyze environmental quality in Dhaka's cityscape, revealing disparities in natural light and greenery affecting mental health across economic classes.

## Contribution

It introduces a novel computer vision pipeline to quantify environmental factors like sky visibility and greenery from street-level images in Dhaka.

## Key findings

- Lower economic classes have reduced sky visibility.
- Higher economic classes lack greenery in their environment.
- Environmental disparities may be mitigated through rent restructuring.

## Abstract

In a densely populated city like Dhaka (Bangladesh), a growing number of high-rise buildings is an inevitable reality. However, they pose mental health risks for citizens in terms of detachment from natural light, sky view, greenery, and environmental landscapes. The housing economy and rent structure in different areas may or may not take account of such environmental factors. In this paper, we build a computer vision based pipeline to study factors like sky visibility, greenery in the sidewalks, and dominant colors present in streets from a pedestrian's perspective. We show that people in lower economy classes may suffer from lower sky visibility, whereas people in higher economy classes may suffer from lack of greenery in their environment, both of which could be possibly addressed by implementing rent restructuring schemes.