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Industrial smoke emissions present a serious threat to natural ecosystems and human health. Prior works have shown that using computer vision techniques to identify smoke is a low cost and convenient method. However, industrial smoke…

Computer Vision and Pattern Recognition · Computer Science 2020-11-11 Yichao Cao , Qingfei Tang , Xiaobo Lu , Fan Li , Jinde Cao

Global ambient air pollution, a transboundary challenge, is typically addressed through interventions relying on data from spatially sparse and heterogeneously placed monitoring stations. These stations often encounter temporal data gaps…

Machine Learning · Computer Science 2024-02-19 Liam J Berrisford , Hugo Barbosa , Ronaldo Menezes

Methane (CH4) emissions estimates from top-down studies over oil and gas basins have revealed systematic under-estimation of CH4 emissions in current national inventories. Sparse but extremely large amounts of CH4 from oil and gas…

Methane is a potent greenhouse gas and a major driver of climate change, making its timely detection critical for effective mitigation. Machine learning (ML) deployed onboard satellites can enable rapid detection while reducing downlink…

Computer Vision and Pattern Recognition · Computer Science 2026-05-14 Maggie Chen , Hala Lamdouar , Luca Marini , Laura Martínez-Ferrer , Chris Bridges , Giacomo Acciarini

Fire outbreaks pose critical threats to human life and infrastructure, necessitating high-fidelity early-warning systems that detect combustion precursors such as smoke. However, smoke plumes exhibit complex spatiotemporal dynamics…

Computer Vision and Pattern Recognition · Computer Science 2025-08-21 Nitish Kumar Mahala , Muzammil Khan , Pushpendra Kumar

Deep learning identification models have shown promise for identifying gas plumes in Longwave IR hyperspectral images of urban scenes, particularly when a large library of gases are being considered. Because many gases have similar spectral…

Computer Vision and Pattern Recognition · Computer Science 2024-01-25 Scout Jarman , Zigfried Hampel-Arias , Adra Carr , Kevin R. Moon

Remote sensors are becoming the standard for observing and recording ecological data in the field. Such sensors can record data at fine temporal resolutions, and they can operate under extreme conditions prohibitive to human access.…

Artificial Intelligence · Computer Science 2012-06-26 Ethan W. Dereszynski , Thomas G. Dietterich

Air quality has major impact on a country's socio-economic position and identifying major air pollution sources is at the heart of tackling the issue. Spatially and temporally distributed air quality data acquisition across a country as…

Machine Learning · Computer Science 2021-01-19 Sivaramakrishnan KN , Lipika Deka , Manik Gupta

Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) was a field campaign aimed at better understanding the impact of wildfires and agricultural fires on air quality and climate. The FIREX-AQ campaign took place in…

Urban air pollution hotspots pose significant health risks, yet their detection and analysis remain limited by the sparsity of public sensor networks. This paper addresses this challenge by combining predictive modeling and mechanistic…

Computers and Society · Computer Science 2025-02-11 Ankit Bhardwaj , Ananth Balashankar , Shiva Iyer , Nita Soans , Anant Sudarshan , Rohini Pande , Lakshminarayanan Subramanian

Mitigating methane emissions is the fastest way to stop global warming in the short-term and buy humanity time to decarbonise. Despite the demonstrated ability of remote sensing instruments to detect methane plumes, no system has been…

We describe a method for detecting, locating and quantifying sources of gas emissions to the atmosphere using remotely obtained gas concentration data; the method is applicable to gases of environmental concern. We demonstrate its…

Applications · Statistics 2015-06-12 Bill Hirst , Philip Jonathan , Fernando Gonzalez del Cueto , David Randell , Oliver Kosut

Industrial accidents, chemical spills, and structural fires can release large amounts of harmful materials that disperse into urban atmospheres and impact populated areas. Computer models are typically used to predict the transport of toxic…

Machine Learning · Computer Science 2024-06-06 Yinan Wang , M. Giselle Fernández-Godino , Nipun Gunawardena , Donald D. Lucas , Xiaowei Yue

Reducing methane emissions is essential for mitigating global warming. To attribute methane emissions to their sources, a comprehensive dataset of methane source infrastructure is necessary. Recent advancements with deep learning on…

Computer Vision and Pattern Recognition · Computer Science 2022-08-16 Bryan Zhu , Nicholas Lui , Jeremy Irvin , Jimmy Le , Sahil Tadwalkar , Chenghao Wang , Zutao Ouyang , Frankie Y. Liu , Andrew Y. Ng , Robert B. Jackson

Climate change may be classified as the most important environmental problem that the Earth is currently facing, and affects all living species on Earth. Given that air-quality monitoring stations are typically ground-based their abilities…

Machine Learning · Computer Science 2023-05-08 Andrew Rowley , Oktay Karakuş

Methane (CH$_4$) is the chief contributor to global climate change. Recent Airborne Visible-Infrared Imaging Spectrometer-Next Generation (AVIRIS-NG) has been very useful in quantitative mapping of methane emissions. Existing methods for…

Image and Video Processing · Electrical Eng. & Systems 2023-04-07 Satish Kumar , Ivan Arevalo , ASM Iftekhar , B S Manjunath

The increasing frequency and severity of wildfires highlight the need for accurate fire and plume spread models. We introduce an approach that effectively isolates and tracks fire and plume behavior across various spatial and temporal…

Computer Vision and Pattern Recognition · Computer Science 2024-12-13 Daryn Sagel , Bryan Quaife

Prioritizing methane for near-term climate action is crucial due to its significant impact on global warming. Previous work used columnwise matched filter products from the airborne AVIRIS-NG imaging spectrometer to detect methane plume…

Signal Processing · Electrical Eng. & Systems 2025-06-10 Vassiliki Mancoridis , Brian Bue , Jake H. Lee , Andrew K. Thorpe , Daniel Cusworth , Alana Ayasse , Philip G. Brodrick , Riley Duren

Air pollution remains one of the most pressing environmental challenges of the modern era, significantly impacting human health, ecosystems, and climate. While traditional air quality monitoring systems provide critical data, their high…

Machine Learning · Computer Science 2025-03-17 Elie Azeraf , Audrey Wagner , Emilie Bialic , Samia Mellah , Ludovic Lelandais

As of 2022, greenhouse gases (GHG) emissions reporting and auditing are not yet compulsory for all companies and methodologies of measurement and estimation are not unified. We propose a machine learning-based model to estimate scope 1 and…

Machine Learning · Computer Science 2022-12-22 Jeremi Assael , Thibaut Heurtebize , Laurent Carlier , François Soupé