Skip to main content Skip to secondary navigation

Assessing brick kilns number, location and use in Bangladesh

Main content start
Map of the locations of brick kilns generated by the machine learning model

Landscape of brick manufacturing in Bangladesh: a scalable approach to deep learning for sustainable development



Leverage advances in machine learning and improvements in satellite imagery to develop a reproducible and automated pipeline that locates and produces a database all of the traditional brick kilns in Bangladesh.



Brick production is central to construction in Bangladesh, resulting in the rapid expansion of brick kilns throughout the country. However, there is no accurate accounting of how many kilns are operating as many are either not counted because they violate various regulations or are never registered, enabling further violations of national regulations. We will use this data to catalyze a discussion among brick kiln owners, government regulators, researchers and civil society. The long-term aim is to motivate progress toward a manufacturing system that generates less environmental and health harm.


Project Dates



Stage of Work

We have currently developed and tested a convolutional neural network that works well at identifying brick kilns in satellite imagery. We are conducting further refinements to the model, as well as developing approaches to isolate where within a given image a kiln is located in order to determine the approximate geographic locations of all kilns.


To Learn More About This Work

A Better Brick: Solving an Airborne Health Threat (Stanford Woods Institute for the Environment)



Primary Contact:  Nina Brooks

Stanford University

.   Stephen Luby

.   Nina Brooks

.   Jihyeon Lee

.   Fahim Tajwar



Stanford Woods Institute for the Environment: Environmental Venture Projects (EVP)