Alexe, M., Bergamaschi, P., Segers, A., Detmers, R., Butz, A., Hasekamp, O., ... & Kort, E.A., 2015, Inverse Modelling of CH 4 Emissions for 2010–2011 Using Different Satellite Retrieval Products from GOSAT and SCIAMACHY, Atmospheric Chemistry and Physics, 15(1), PP. 113-133, https://doi.org/ 10.5194/acp-15-113-2015, 2015.
Aumann, H.H., Chahine, M.T., Gautier, C., Goldberg, M.D., Kalnay, E., McMillin, L.M., ... & Susskind, J., 2003, AIRS/AMSU/HSB on the Aqua Mission: Design, Science Objectives, Data Products, and Processing Systems, IEEE Transactions on Geoscience and Remote Sensing, 41(2), PP. 253-264, DOI: 10.1109/ TGRS.2002.808356.
Bagheri, R., Ebrahimi Bouzani, M. & Mokhtari Malekabadi, R., 2022, Spatial Distribution and Deprivation Zoning in Isfahan City, Geography (Scientific Quarterly of the Iranian Geographical Association), 20(73), PP. 37-62.
Basu, S., Lan, X., Dlugokencky, E., Michel, S., Schwietzke, S., Miller, J.B., ... & Manca, G., 2022, Estimating Emissions of Methane Consistent with Atmospheric Measurements of Methane and δ 13 C of Methane, Atmospheric Chemistry and Physics, 22(23), PP. 15351-15377, https://doi.org/10.5194/acp-22-15351-2022.
Batur, I., Markolf, S.A., Chester, M.V., Middel, A., Hondula, D. & Vanos, J., 2022,
Street-Level Heat and Air Pollution Exposure Informed by Mobile Sensing, Transportation Research Part D: Transport and Environment, 113, P. 103535,
https://doi.org/10.1016/j.trd.2022.103535.
Cherepanova, E.V., Feoktistova, N.V. & Chudakova, M.A., 2020, Analysis of Methane Concentration Anomalies over Burned Areas of the Boreal and Arctic Zone of Eastern Siberia in 2018–2019 Using TROPOMI Data, Izvestiya, Atmospheric and Oceanic Physics, 56, PP. 1470-1481, https://doi.org/10.1134/S0001433820120385.
De Gouw, J.A., Veefkind, J.P., Roosenbrand, E., Dix, B., Lin, J.C., Landgraf, J. & Levelt, P.F., 2020, Daily Satellite Observations of Methane from Oil and Gas Production Regions in the United States, Scientific Reports, 10(1), P. 1379, https://doi.org/ 10.1038/s41598-020-57678-4.
Filonchyk, M., Yan, H., Yang, S. & Lu, X., 2018, Detection of Aerosol Pollution Sources during Sandstorms in Northwestern China Using Remote Sensed and Model Simulated Data, Advances in Space Research, 61(4), PP. 1035-1046, https://doi.org/10.1016/j.asr.2017.11.037.
Garajeh, M.K. & Feizizadeh, B., 2021, A Comparative Approach of Data-Driven Split-Window Algorithms and MODIS Products for Land Surface Temperature Retrieval, Applied Geomatics, 13, PP. 715-733, https://doi.org/10.1007/s12518-021-00388-x.
Giovannini, L., Ferrero, E., Karl, T., Rotach, M.W., Staquet, C., Trini Castelli, S. & Zardi, D., 2020, Atmospheric Pollutant Dispersion over Complex Terrain: Challenges and Needs for Improving Air Quality Measurements and Modeling, Atmosphere, 11(6), P. 646, https://doi.org/ 10.3390/atmos11060646.
Google Earth Engine, 2024, COPERNICUS/ S5P/OFFL/L3_CH4: TROPOMI CH4: Offline. Google Earth Engine. https://developers.google.com/earth-engine/datasets/catalog/COPERNICUS_S5P_OFFL_L3_CH4.
Hadian, A. & Moradizadeh, M., 2024, Modeling the Distribution of NO₂ and O₃ Pollutant Concentrations with Appropriate Spatial Resolution Using Integrated Ground and Satellite Data, Journal of Remote Sensing and GIS of Iran, 16(2), PP. 85-104, DOI: 10.48308/gisj.2023.103726.
Jin, Z., He, J. & Wang, W., 2024, Monitoring Methane Concentrations with High Spatial Resolution over China by Using Random Forest Model, Remote Sensing, 16(14), P. 2525, https://doi.org/10.3390/ rs16142525.
Kazemi Garajeh, M., Laneve, G., Rezaei, H., Sadeghnejad, M., Mohamadzadeh, N. & Salmani, B., 2023, Monitoring Trends of CO, NO2, SO2, and O3 Pollutants Using Time-Series Sentinel-5 Images Based on Google Earth Engine, Pollutants, 3(2), PP. 255-279, https://doi.org/10.3390/pollutants3020019.
Li, Y. & Fang, H., 2022, Real-Time Software for the Efficient Generation of the Clumping Index and Its Application Based on the Google Earth Engine, Remote Sensing, 14(15), P. 3837, https://doi.org/10.3390/rs14153837.
Loyola, D.G., Gimeno García, S., Lutz, R., Argyrouli, A., Romahn, F., Spurr, R.J., ... & Schüssler, O., 2018, The Operational Cloud Retrieval Algorithms from TROPOMI on Board Sentinel-5 Precursor, Atmospheric Measurement Techniques, 11(1), PP. 409-427, https://doi.org/ 10.5194/amt-11-409-2018.
Ma, L., Cui, Y., Liu, B., Liao, B., Wei, J., Han, H. & Tian, W., 2023, A GIS-Based Method for Modeling Methane Emissions from Paddy Fields by Fusing Multiple Sources of Data, Science of The Total Environment, 859, P. 159917, https://doi.org/ 10.1016/j.scitotenv. 2022.159917.
Mohammadi, M. & Akhoundzadeh Henzaei, M., 2022, Monitoring and Detection of Methane Gas in Tehran Using Google Earth Engine Platform, Geoinformatics in Civil Engineering, 1(1), PP. 41-52, DOI: 10.22061/jrsgr.2022.1948.
Mousavi, S.M., Falahatkar, S. & Farajzadeh, M., 2017, Monitoring Monthly and Seasonal Changes of Methane Gas Using GOSAT Satellite Data, Journal of Physical Geography Research, 49(2), PP. 327-340, DOI: 10.22059/jphgr.2017.62848.
Mukundan, A., Huang, C.C., Men, T.C., Lin, F.C. & Wang, H.C., 2022,
Air Pollution Detection Using a Novel Snap-Shot Hyperspectral Imaging Technique, Sensors, 22(16), P. 6231,
https://doi.org/ 10.3390/s22166231.
Naboureh, A., Li, A., Bian, J. & Lei, G., 2023, National Scale Land Cover Classification Using the Semiautomatic High-Quality Reference Sample Generation (HRSG) Method and an Adaptive Supervised Classification Scheme, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 16, PP. 1858-1870, 10.1109/JSTARS.2023.3241620.
Nooraie, H. & Shokrani, S.M., 2021, Spatial Analysis and Classification of the Fifteen Regions of Isfahan Metropolis Based on Air Pollution Distribution, Geography and Environmental Planning, 32(2), PP. 83-102, DOI: 10.22108/gep.2021.126981.1394.
Orsetti, E., Tollin, N., Lehmann, M., Valderrama, V.A. & Morató, J., 2022,
Building Resilient Cities: Climate Change and Health Interlinkages in the Planning of Public Spaces, International Journal of Environmental Research and Public Health, 19(3), P. 1355,
https://doi.org/10.3390/ ijerph19031355.
Pei, Z., Han, G., Mao, H., Chen, C., Shi, T., Yang, K., ... & Gong, W., 2023,
Improving Quantification of Methane Point Source Emissions from Imaging Spectroscopy, Remote Sensing of Environment, 295, P. 113652,
https://doi.org/10.1016/j.rse.2023. 113652.
Plant, G., Kort, E.A., Murray, L.T., Maasakkers, J.D. & Aben, I., 2022, Evaluating Urban Methane Emissions from Space Using TROPOMI Methane and Carbon Monoxide Observations, Remote Sensing of Environment, 268, P. 112756, https://doi.org/10.1016/j.rse.2021.112756.
Sadavarte, P., Pandey, S., Maasakkers, J.D., Lorente, A., Borsdorff, T., Denier van der Gon, H., ... & Aben, I., 2021, Methane Emissions from Superemitting Coal Mines in Australia Quantified Using TROPOMI Satellite Observations, Environmental Science & Technology, 55(24), PP. 16573-16580, https://doi.org/ 10.1021/acs.est.1c03976.
Shikwambana, L., Mhangara, P. & Mbatha, N., 2020, Trend Analysis and First Time Observations of Sulphur Dioxide and Nitrogen Dioxide in South Africa Using TROPOMI/Sentinel-5 P Data, International Journal of Applied Earth Observation and Geoinformation, 91, P. 102130.
Skeie, R.B., Hodnebrog, Ø. & Myhre, G., 2023, Trends in Atmospheric Methane Concentrations since 1990 Were Driven and Modified by Anthropogenic Emissions, Communications Earth & Environment, 4(1), P. 317, https://doi.org/ 10.1016/j.jag.2020.102130.
Song, H., Sheng, M., Lei, L., Guo, K., Zhang, S. & Ji, Z., 2023,
Spatial and Temporal Variations of Atmospheric CH4 in Monsoon Asia Detected by Satellite Observations of GOSAT and TROPOMI, Remote Sensing, 15(13), P. 3389,
https://doi.org/10.3390/rs15133389.
Vîrghileanu, M., Săvulescu, I., Mihai, B.A., Nistor, C. & Dobre, R., 2020, Nitrogen Dioxide (NO2) Pollution Monitoring with Sentinel-5P Satellite Imagery over Europe during the Coronavirus Pandemic Outbreak, Remote Sensing, 12(21), P. 3575, https://doi.org/10.3390/rs12213575.
Vlasov, D., Ramírez, O. & Luhar, A., 2022, Road Dust in Urban and Industrial Environ-ments: Sources, Pollutants, Impacts, and Management, Atmosphere, 13(4), P. 607, https://doi.org/10.3390/atmos13040607.