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A new achievement of satellite-based gas flaring volume estimation: decision tree modeling

Gas flaring (GF) is a long-term issue in the oil/gas industries and has a critical effect on the environment. In the last decade, remote sensing technology has shown resounding capabilities to detect and characterize GF. Iran has many natural oil/gas processing plants and petrochemical companies tha...

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Published in:Earth science informatics 2024-08, Vol.17 (4), p.2887-2901
Main Authors: Asadi-Fard, Elmira, Falahatkar, Samereh, Tanha Ziyarati, Mahdi, Zhang, Xiaodong
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Falahatkar, Samereh
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Zhang, Xiaodong
description Gas flaring (GF) is a long-term issue in the oil/gas industries and has a critical effect on the environment. In the last decade, remote sensing technology has shown resounding capabilities to detect and characterize GF. Iran has many natural oil/gas processing plants and petrochemical companies that are located in the southern regions. The main goal of this research is estimation of the volume of GF for two years (2018–2019) by day/nighttime radiation and air pollutant data. We used Decision Tree modeling/Exhaustive CHAID (Chi-squared Automatic Interaction Detector) based on remote sensing data such as shortwave infrared (SWIR) and thermal infrared (TIR) of Landsat 8/ M10 of VIIRS (Visible Infrared Imaging Radiometer Suite) / air pollutants of TROPOMI (Tropospheric Monitoring Instrument) in three types of models. Results showed that R 2 values for model 1 (based on all variables/SWIR, TIR, Pollution products), model 2 (based on SWIR bands and pollution data), and model 3 (based on SWIR and TIR bands) is 0.52, 0.50, and 0.51, respectively. The results of sensitivity analysis showed that the shortwave infrared band for two sensors OLI (Operational Land Imager) /VIIRS (Visible Infrared Imaging Radiometer Suite) had the most important role in the estimation of gas flaring volume. The valuable findings of this research represent the important effect of the shortwave infrared bands of the sensors in estimating the GF volume at the local/global scale by hierarchical decision scheme modeling.
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subjects Air monitoring
Air pollution
Decision trees
Earth and Environmental Science
Earth Sciences
Earth System Sciences
Environmental effects
Estimation
Imaging radiometers
Information Systems Applications (incl.Internet)
Infrared analysis
Infrared detectors
Infrared imaging
Infrared radiometers
Infrared spectra
Landsat
Modelling
Monitoring instruments
Oil and gas industry
Ontology
Petrochemicals
Pollutants
Radiometry
Remote sensing
Sensitivity analysis
Sensors
Short wave radiation
Simulation and Modeling
Space Exploration and Astronautics
Space Sciences (including Extraterrestrial Physics
title A new achievement of satellite-based gas flaring volume estimation: decision tree modeling
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