mlsanityData to 7 Oct 2026

Brick Kiln Dataset for Pakistan's IGP Region Using AI

arXiv 2412.00052 ↗First posted 24 Nov 2024cs.CVcited by 1

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Abstract (arXiv)

Brick kilns are a major source of air pollution in Pakistan, with many operating without regulation. A key challenge in Pakistan and across the Indo-Gangetic Plain is the limited air quality monitoring and lack of transparent data on pollution sources. To address this, we present a two-fold AI approach that combines low-resolution Sentinel-2 and high-resolution imagery to map brick kiln locations. Our process begins with a low-resolution analysis, followed by a post-processing step to reduce false positives, minimizing the need for extensive high-resolution imagery. This analysis initially identified 20,000 potential brick kilns, with high-resolution validation confirming around 11,000 kilns. The dataset also distinguishes between Fixed Chimney and Zigzag kilns, enabling more accurate pollution estimates for each type. Our approach demonstrates how combining satellite imagery with AI can effectively detect specific polluting sources. This dataset provides regulators with insights into brick kiln pollution, supporting interventions for unregistered kilns and actions during high pollution episodes.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 3 of its 39 references that are in the map. First posted on arXiv 24 Nov 2024.

Builds on

3 of 39 references.

References · 3

  1. 2020Oriented Object Detection in Aerial Images with Box Boundary-Aware Vectorscited by 63
  2. 2024Scalable Methods for Brick Kiln Detection and Compliance Monitoring from Satellite Imagery: A Deployment Case Study in Indiacited by 3
  3. 2023Mitigating climate and health impact of small-scale kiln industry using multi-spectral classifier and deep learningcited by 1

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Citing papers per year: 2024: 1.

1 paper.