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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 |
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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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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.</description><identifier>ISSN: 1865-0473</identifier><identifier>EISSN: 1865-0481</identifier><identifier>DOI: 10.1007/s12145-024-01316-4</identifier><language>eng</language><publisher>Berlin/Heidelberg: Springer Berlin Heidelberg</publisher><subject>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</subject><ispartof>Earth science informatics, 2024-08, Vol.17 (4), p.2887-2901</ispartof><rights>The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c270t-1aaba9ad71fa50d9ce3d32573467b7d370c78be1e5c5e59b4780f8aa4fb262e13</cites><orcidid>0000-0001-9283-0201</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Asadi-Fard, Elmira</creatorcontrib><creatorcontrib>Falahatkar, Samereh</creatorcontrib><creatorcontrib>Tanha Ziyarati, Mahdi</creatorcontrib><creatorcontrib>Zhang, Xiaodong</creatorcontrib><title>A new achievement of satellite-based gas flaring volume estimation: decision tree modeling</title><title>Earth science informatics</title><addtitle>Earth Sci Inform</addtitle><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.</description><subject>Air monitoring</subject><subject>Air pollution</subject><subject>Decision trees</subject><subject>Earth and Environmental Science</subject><subject>Earth Sciences</subject><subject>Earth System Sciences</subject><subject>Environmental effects</subject><subject>Estimation</subject><subject>Imaging radiometers</subject><subject>Information Systems Applications (incl.Internet)</subject><subject>Infrared analysis</subject><subject>Infrared detectors</subject><subject>Infrared imaging</subject><subject>Infrared radiometers</subject><subject>Infrared spectra</subject><subject>Landsat</subject><subject>Modelling</subject><subject>Monitoring instruments</subject><subject>Oil and gas industry</subject><subject>Ontology</subject><subject>Petrochemicals</subject><subject>Pollutants</subject><subject>Radiometry</subject><subject>Remote sensing</subject><subject>Sensitivity analysis</subject><subject>Sensors</subject><subject>Short wave radiation</subject><subject>Simulation and Modeling</subject><subject>Space Exploration and Astronautics</subject><subject>Space Sciences (including Extraterrestrial Physics</subject><issn>1865-0473</issn><issn>1865-0481</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9UMtOwzAQtBBIVKU_wMkS54DXdmKXW1XxkipxgQsXy443JSiPYidF_D0uQXDjtKPVzOzOEHIO7BIYU1cROMg8Y1xmDAQUmTwiM9BFWkkNx79YiVOyiLF2TAAvBOd6Rl5WtMMPasvXGvfYYjfQvqLRDtg09YCZsxE93dpIq8aGutvSfd-MLVKMQ93aoe67a-qxrGNCdAiItO09Nol5Rk4q20Rc_Mw5eb69eVrfZ5vHu4f1apOVXLEhA2udXVqvoLI588sShRc8V0IWyikvFCuVdgiYlznmSyeVZpW2VlaOFxxBzMnF5LsL_fuY_jJv_Ri6dNIIYIUutGQssfjEKkMfY8DK7EIKED4NMHOo0Uw1mlSj-a7RyCQSkyjuDtkx_Fn_o_oC8Uh13w</recordid><startdate>20240801</startdate><enddate>20240801</enddate><creator>Asadi-Fard, Elmira</creator><creator>Falahatkar, Samereh</creator><creator>Tanha Ziyarati, Mahdi</creator><creator>Zhang, Xiaodong</creator><general>Springer Berlin Heidelberg</general><general>Springer Nature B.V</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7TG</scope><scope>8FD</scope><scope>JQ2</scope><scope>KL.</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><orcidid>https://orcid.org/0000-0001-9283-0201</orcidid></search><sort><creationdate>20240801</creationdate><title>A new achievement of satellite-based gas flaring volume estimation: decision tree modeling</title><author>Asadi-Fard, Elmira ; 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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.</abstract><cop>Berlin/Heidelberg</cop><pub>Springer Berlin Heidelberg</pub><doi>10.1007/s12145-024-01316-4</doi><tpages>15</tpages><orcidid>https://orcid.org/0000-0001-9283-0201</orcidid></addata></record> |
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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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