Eye in the Sky: Detection and Compliance Monitoring of Brick Kilns using Satellite Imagery
Rishabh Mondal, Shataxi Dubey, Vannsh Jani, Shrimay Shah, Suraj, Jaiswal, Zeel B Patel, Nipun Batra

TL;DR
This paper presents a scalable satellite imagery-based framework using open data and machine learning to detect brick kilns and assess their compliance with environmental and safety policies in India.
Contribution
It introduces a novel, open-data approach combining Google Maps API and YOLOv8x for large-scale detection and compliance monitoring of brick kilns.
Findings
Detected 19,579 brick kilns across 9 states.
Many kilns do not comply with safety and environmental policies.
Framework can be used by governments for enforcement and regulation.
Abstract
Air pollution kills 7 million people annually. The brick manufacturing industry accounts for 8%-14% of air pollution in the densely populated Indo-Gangetic plain. Due to the unorganized nature of brick kilns, policy violation detection, such as proximity to human habitats, remains challenging. While previous studies have utilized computer vision-based machine learning methods for brick kiln detection from satellite imagery, they utilize proprietary satellite data and rarely focus on compliance with government policies. In this research, we introduce a scalable framework for brick kiln detection and automatic compliance monitoring. We use Google Maps Static API to download the satellite imagery followed by the YOLOv8x model for detection. We identified and hand-verified 19579 new brick kilns across 9 states within the Indo-Gangetic plain. Furthermore, we automate and test the compliance…
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Taxonomy
TopicsRemote-Sensing Image Classification · 3D Surveying and Cultural Heritage
MethodsFocus
