23.2.22 Atmospheric, Aerosols, Aerosol Optical Depth, Measurements, Remote Sensing

You, Y., Lu, C., Wang, W., Tang, C.,
Relative CNN-RNN: Learning Relative Atmospheric Visibility From Images,
IP(28), No. 1, January 2019, pp. 45-55.
IEEE DOI 1810
Atmospheric modeling, Atmospheric measurements, Estimation, Meteorology, Observatories, Support vector machines, large-scale image collection BibRef

Rushton, C.[Christopher], Galatioto, F.[Fabio], Wright, J.[James], Nielsen, E.[Erik], Tsotskas, C.[Christos],
City-wide emissions modelling using fleet probe vehicles,
IET-ITS(12), No. 9, November 2018, pp. 1181-1188.
DOI Link 1810
BibRef

Liu, L.[Li], Mishchenko, M.I.[Michael I.],
Scattering and Radiative Properties of Morphologically Complex Carbonaceous Aerosols: A Systematic Modeling Study,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Behera, S.K., Dash, A.K., Dogra, D.P., Roy, P.P.,
Air Signature Recognition Using Deep Convolutional Neural Network-Based Sequential Model,
ICPR18(3525-3530)
IEEE DOI 1812
Feature extraction, Convolutional neural networks, Convolution, Atmospheric modeling BibRef

Xu, H., Chen, Y., Wang, L.,
Cross-Track Infrared Sounder Spectral Gap Filling Toward Improving Intercalibration Uncertainties,
GeoRS(57), No. 1, January 2019, pp. 509-519.
IEEE DOI 1901
Calibration, Atmospheric measurements, Instruments, Atmospheric modeling, Extraterrestrial measurements, spectrum gap filling BibRef

She, L., Xue, Y., Yang, X., Leys, J., Guang, J., Che, Y., Fan, C., Xie, Y., Li, Y.,
Joint Retrieval of Aerosol Optical Depth and Surface Reflectance Over Land Using Geostationary Satellite Data,
GeoRS(57), No. 3, March 2019, pp. 1489-1501.
IEEE DOI 1903
aerosols, atmospheric optics, geophysical signal processing, radiative transfer, remote sensing, aerosol optical depth, optimal estimation BibRef

Xie, Y., Xue, Y., Guang, J., Mei, L., She, L., Li, Y., Che, Y., Fan, C.,
Deriving a Global and Hourly Data Set of Aerosol Optical Depth Over Land Using Data From Four Geostationary Satellites: GOES-16, MSG-1, MSG-4, and Himawari-8,
GeoRS(58), No. 3, March 2020, pp. 1538-1549.
IEEE DOI 2003
Aerosols, Monitoring, Geostationary satellites, Remote sensing, Earth, Optical sensors, Aerosol optical depth (AOD), MSG-4 BibRef

Schuster, G.L.[Gregory L.], Espinosa, W.R.[W. Reed], Ziemba, L.D.[Luke D.], Beyersdorf, A.J.[Andreas J.], Rocha-Lima, A.[Adriana], Anderson, B.E.[Bruce E.], Martins, J.V.[Jose V.], Dubovik, O.[Oleg], Ducos, F.[Fabrice], Fuertes, D.[David], Lapyonok, T.[Tatyana], Shook, M.[Michael], Derimian, Y.[Yevgeny], Moore, R.H.[Richard H.],
A Laboratory Experiment for the Statistical Evaluation of Aerosol Retrieval (STEAR) Algorithms,
RS(11), No. 5, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Ravindrababu, S., Ratnam, M.V.[M. Venkat], Basha, G.[Ghouse], Liou, Y.A.[Yuei-An], Reddy, N.N.[N. Narendra],
Large Anomalies in the Tropical Upper Troposphere Lower Stratosphere (UTLS) Trace Gases Observed during the Extreme 2015-16 El Niño Event by Using Satellite Measurements,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Fan, X.L.[Xian-Lei], Qu, Y.[Ying],
Retrieval of High Spatial Resolution Aerosol Optical Depth from HJ-1 A/B CCD Data,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Xu, F.[Feng], Diner, D.J.[David J.], Dubovik, O.[Oleg], Schechner, Y.Y.[Yoav Y.],
A Correlated Multi-Pixel Inversion Approach for Aerosol Remote Sensing,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Shi, Z.[Zheng], Xing, T.Y.[Ting-Yan], Guang, J.[Jie], Xue, Y.[Yong], Che, Y.H.[Ya-Hui],
Aerosol Optical Depth over the Arctic Snow-Covered Regions Derived from Dual-Viewing Satellite Observations,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Dongre, P.K.[Prateek Kumar], Havemann, S.[Stephan], Hargrave, P.[Peter], Orlando, A.[Angiola], Sudiwala, R.[Rashmikant], Thomas, C.[Christopher], Goldie, D.[David], Withington, S.[Stafford],
End-to-End Instrument Performance Simulation System (EIPS) Framework: Application to Satellite Microwave Atmospheric Sounding Systems,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Kurmi, I.[Indrajit], Schedl, D.C.[David C.], Bimber, O.[Oliver],
Thermal Airborne Optical Sectioning,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Deng, G.R.[Guo-Rong], Zhang, H.Y.[Hong-Yan], Guo, X.Y.[Xiao-Yi], Shan, Y.[Yu], Ying, H.[Hong], Rihan, W.[Wu], Li, H.[Hui], Han, Y.L.[Yang-Li],
Asymmetric Effects of Daytime and Nighttime Warming on Boreal Forest Spring Phenology,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Li, W.Z.[Wen-Zhao], Ali, E.[Elham], El-Magd, I.A.[Islam Abou], Mourad, M.M.[Moustafa Mohamed], El-Askary, H.[Hesham],
Studying the Impact on Urban Health over the Greater Delta Region in Egypt Due to Aerosol Variability Using Optical Characteristics from Satellite Observations and Ground-Based AERONET Measurements,
RS(11), No. 17, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Zhang, W.Z.[Wen-Zhong], Deng, S.M.[Shu-Mei], Luo, T.[Tao], Wu, Y.[Yang], Liu, N.[Nana], Li, X.B.[Xue-Bin], Huang, Y.B.[Yin-Bo], Zhu, W.[Wenyue],
New Global View of Above-Cloud Absorbing Aerosol Distribution Based on CALIPSO Measurements,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Mei, L., Rozanov, V., Jethva, H., Meyer, K.G., Lelli, L., Vountas, M., Burrows, J.P.,
Extending XBAER Algorithm to Aerosol and Cloud Condition,
GeoRS(57), No. 10, October 2019, pp. 8262-8275.
IEEE DOI 1910
aerosols, atmospheric optics, atmospheric techniques, clouds, dust, radiative transfer, radiometers, remote sensing, cloud condition, satellite BibRef

Klimov, P.[Pavel], Khrenov, B.[Boris], Kaznacheeva, M.[Margarita], Garipov, G.[Gali], Panasyuk, M.[Mikhail], Petrov, V.[Vasily], Sharakin, S.[Sergei], Shirokov, A.[Andrei], Yashin, I.[Ivan], Zotov, M.[Mikhail], Grebenyuk, V.[Viktor], Grinyuk, A.[Andrei], Lavrova, M.[Maria], Tkachenko, A.[Artur], Tkachev, L.[Leonid], Botvinko, A.[Alla], Saprykin, O.[Oleg], Puchkov, A.[Andrei], Senkovsky, A.[Alexander],
Remote Sensing of the Atmosphere by the Ultraviolet Detector TUS Onboard the Lomonosov Satellite,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
BibRef

Fan, C.[Cheng], Fu, G.L.[Guang-Liang], di Noia, A.[Antonio], Smit, M.[Martijn], Rietjens, J.H.H.[Jeroen H.H.], Ferrare, R.A.[Richard A.], Burton, S.[Sharon], Li, Z.Q.[Zheng-Qiang], Hasekamp, O.P.[Otto P.],
Use of A Neural Network-Based Ocean Body Radiative Transfer Model for Aerosol Retrievals from Multi-Angle Polarimetric Measurements,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Malmgren-Hansen, D.[David], Laparra, V.[Valero], Nielsen, A.A.[Allan Aasbjerg], Camps-Valls, G.[Gustau],
Statistical retrieval of atmospheric profiles with deep convolutional neural networks,
PandRS(158), 2019, pp. 231-240.
Elsevier DOI 1912
Atmospheric measurements, Neural networks, Infrared measurements, Information retrieval BibRef

Rosenkranz, P.W., Cimini, D.,
Speed Dependence of 22- and 118-GHz Line Shapes for Tropospheric Remote Sensing,
GeoRS(57), No. 12, December 2019, pp. 9702-9708.
IEEE DOI 1912
Shape, Absorption, Doppler effect, Atmospheric measurements, Atmosphere, Resonant frequency, Remote sensing, spectral shape BibRef

She, L.[Lu], Zhang, H.[Hankui], Wang, W.[Weile], Wang, Y.J.[Yu-Jie], Shi, Y.[Yun],
Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Ceamanos, X.[Xavier], Moparthy, S.[Suman], Carrer, D.[Dominique], Seidel, F.C.[Felix C.],
Assessing the Potential of Geostationary Satellites for Aerosol Remote Sensing Based on Critical Surface Albedo,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Li, L.[Lianfa],
Optimal Inversion of Conversion Parameters from Satellite AOD to Ground Aerosol Extinction Coefficient Using Automatic Differentiation,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Zhao, L.[Lewen], Václavovic, P.[Pavel], Douša, J.[Jan],
Performance Evaluation of Troposphere Estimated from Galileo-Only Multi-Frequency Observations,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Wang, W.Y.[Wen-Yu], Wang, Z.Z.[Zhen-Zhan], Duan, Y.Q.[Yong-Qiang],
Preliminary Evaluation of the Error Budgets in the TALIS Measurements and Their Impact on the Retrievals,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
THz Atmospheric Limb Sounder. Measure atmosphere. BibRef

Siomos, N.[Nikolaos], Fountoulakis, I.[Ilias], Natsis, A.[Athanasios], Drosoglou, T.[Theano], Bais, A.[Alkiviadis],
Automated Aerosol Classification from Spectral UV Measurements Using Machine Learning Clustering,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003
BibRef

Zou, B.[Bin], Liu, N.[Ning], Wang, W.[Wei], Feng, H.H.[Hui-Hui], Liu, X.P.[Xiang-Ping], Lin, Y.[Yan],
An Effective and Efficient Enhanced Fixed Rank Smoothing Method for the Spatiotemporal Fusion of Multiple-Satellite Aerosol Optical Depth Products,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Zawadzka-Manko, O.[Olga], Stachlewska, I.S.[Iwona S.], Markowicz, K.M.[Krzysztof M.],
Near-Real-Time Application of SEVIRI Aerosol Optical Depth Algorithm,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Li, C.[Chong], Li, J.[Jing], Dubovik, O.[Oleg], Zeng, Z.C.[Zhao-Cheng], Yung, Y.L.[Yuk L.],
Impact of Aerosol Vertical Distribution on Aerosol Optical Depth Retrieval from Passive Satellite Sensors,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Zhang, T.[Taixin], Zang, L.[Lin], Mao, F.Y.[Fei-Yue], Wan, Y.C.[You-Chuan], Zhu, Y.N.[Yan-Nian],
Evaluation of Himawari-8/AHI, MERRA-2, and CAMS Aerosol Products over China,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
BibRef

Mei, L., Rozanov, V., Ritter, C., Heinold, B., Jiao, Z., Vountas, M., Burrows, J.P.,
Retrieval of Aerosol Optical Thickness in the Arctic Snow-Covered Regions Using Passive Remote Sensing: Impact of Aerosol Typing and Surface Reflection Model,
GeoRS(58), No. 7, July 2020, pp. 5117-5131.
IEEE DOI 2006
Aerosols, Arctic, Clouds, Optical surface waves, Satellites, Sea surface, Remote sensing, Aerosol, arctic, retrieval, satellite, snow-covered BibRef

Zhang, M.[Miao], Su, B.[Bo], Bilal, M.[Muhammad], Atique, L.[Luqman], Usman, M.[Muhammad], Qiu, Z.F.[Zhong-Feng], Ali, M.A.[Md. Arfan], Han, G.[Ge],
An Investigation of Vertically Distributed Aerosol Optical Properties over Pakistan Using CALIPSO Satellite Data,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Camps, A.[Adriano], Alonso-Arroyo, A.[Alberto], Park, H.[Hyuk], Onrubia, R.[Raul], Pascual, D.[Daniel], Querol, J.[Jorge],
L-Band Vegetation Optical Depth Estimation Using Transmitted GNSS Signals: Application to GNSS-Reflectometry and Positioning,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Hoque, H.M.S.[Hossain Mohammed Syedul], Irie, H.[Hitoshi], Damiani, A.[Alessandro], Momoi, M.[Masahiro],
Primary Evaluation of the GCOM-C Aerosol Products at 380 nm Using Ground-Based Sky Radiometer Observations,
RS(12), No. 16, 2020, pp. xx-yy.
DOI Link 2008
BibRef

González, J.A.[Josep-Abel], Calbó, J.[Josep],
Assessing Rapid Variability in Atmospheric Apparent Optical Depth with an Array Spectrometer System,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Song, Z.G.[Zi-Geng], He, X.Q.[Xian-Qiang], Bai, Y.[Yan], Wang, D.F.[Di-Feng], Hao, Z.Z.[Zeng-Zhou], Gong, F.[Fang], Zhu, Q.K.[Qian-Kun],
Changes and Predictions of Vertical Distributions of Global Light-Absorbing Aerosols Based on CALIPSO Observation,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Remer, L.A.[Lorraine A.], Levy, R.C.[Robert C.], Mattoo, S.[Shana], Tanré, D.[Didier], Gupta, P.[Pawan], Shi, Y.X.[Ying-Xi], Sawyer, V.[Virginia], Munchak, L.A.[Leigh A.], Zhou, Y.P.[Ya-Ping], Kim, M.[Mijin], Ichoku, C.[Charles], Patadia, F.[Falguni], Li, R.R.[Rong-Rong], Gassó, S.[Santiago], Kleidman, R.G.[Richard G.], Holben, B.N.[Brent N.],
The Dark Target Algorithm for Observing the Global Aerosol System: Past, Present, and Future,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009
BibRef

Barreto, Á.[África], García, O.E.[Omaira Elena], Schneider, M.[Matthias], García, R.D.[Rosa Delia], Hase, F.[Frank], Sepúlveda, E.[Eliezer], Almansa, A.F.[Antonio Fernando], Cuevas, E.[Emilio], Blumenstock, T.[Thomas],
Spectral Aerosol Optical Depth Retrievals by Ground-Based Fourier Transform Infrared Spectrometry,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Brisco, B.[Brian], Mahdianpari, M.[Masoud], Mohammadimanesh, F.[Fariba],
Hybrid Compact Polarimetric SAR for Environmental Monitoring with the RADARSAT Constellation Mission,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Galtier, S.[Sandrine], Pivard, C.[Clément], Rairoux, P.[Patrick],
Towards DCS in the UV Spectral Range for Remote Sensing of Atmospheric Trace Gases,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Sasi, S.[Sruthy], Natraj, V.[Vijay], García, V.M.[Víctor Molina], Efremenko, D.S.[Dmitry S.], Loyola, D.[Diego], Doicu, A.[Adrian],
Model Selection in Atmospheric Remote Sensing with an Application to Aerosol Retrieval from DSCOVR/EPIC, Part 1: Theory,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Sasi, S.[Sruthy], Natraj, V.[Vijay], García, V.M.[Víctor Molina], Efremenko, D.S.[Dmitry S.], Loyola, D.[Diego], Doicu, A.[Adrian],
Model Selection in Atmospheric Remote Sensing with Application to Aerosol Retrieval from DSCOVR/EPIC. Part 2: Numerical Analysis,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Zhao, M., Si, F., Wang, Y., Zhou, H., Wang, S., Jiang, Y., Liu, W.,
First Year On-Orbit Calibration of the Chinese Environmental Trace Gas Monitoring Instrument Onboard GaoFen-5,
GeoRS(58), No. 12, December 2020, pp. 8531-8540.
IEEE DOI 2012
Electromagnetic interference, Calibration, Monitoring, Instruments, Radiometry, Optical sensors, Earth, Calibration, solar diffusers (SDs) BibRef

Go, S.J.[Su-Jung], Kim, J.[Jhoon], Park, S.S.[Sang Seo], Kim, M.[Mijin], Lim, H.K.[Hyun-Kwang], Kim, J.Y.[Ji-Young], Lee, D.W.[Dong-Won], Im, J.H.[Jung-Ho],
Synergistic Use of Hyperspectral UV-Visible OMI and Broadband Meteorological Imager MODIS Data for a Merged Aerosol Product,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012
BibRef

She, L.[Lu], Zhang, H.K.[Hankui K.], Li, Z.Q.[Zheng-Qiang], de Leeuw, G.[Gerrit], Huang, B.[Bo],
Himawari-8 Aerosol Optical Depth (AOD) Retrieval Using a Deep Neural Network Trained Using AERONET Observations,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Yang, F.[Fukun], Fan, M.[Meng], Tao, J.H.[Jin-Hua],
An Improved Method for Retrieving Aerosol Optical Depth Using Gaofen-1 WFV Camera Data,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Doicu, A.[Adrian], Efremenko, D.S.[Dmitry S.], Trautmann, T.[Thomas],
A Proof-of-Concept Algorithm for the Retrieval of Total Column Amount of Trace Gases in a Multi-Dimensional Atmosphere,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Huang, J.T.[Jing-Ting], Arnott, W.P.[William Patrick], Barnard, J.C.[James C.], Holmes, H.A.[Heather A.],
Theoretical Uncertainty Analysis of Satellite Retrieved Aerosol Optical Depth Associated with Surface Albedo and Aerosol Optical Properties,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Choi, W.[Wonei], Lee, H.[Hanlim], Park, J.[Jeonghyeon],
A First Approach to Aerosol Classification Using Space-Borne Measurement Data: Machine Learning-Based Algorithm and Evaluation,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Nicolae, A.[Ajtai], Alexandru, M.[Mereuta], Horatiu, S.[Stefanie], Andrei, R.[Radovici], Camelia, B.[Botezan], Olga, Z.M.[Zawadzka-Manko], Stachlewska, I.S.[Iwona S.], Kerstin, S.[Stebel], Claus, Z.[Zehner],
SEVIRI Aerosol Optical Depth Validation Using AERONET and Intercomparison with MODIS in Central and Eastern Europe,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
BibRef

Várnai, T.[Tamás], Marshak, A.[Alexander],
Analysis of Near-Cloud Changes in Atmospheric Aerosols Using Satellite Observations and Global Model Simulations,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Lin, J.Y.[Jian-Yu], Zheng, Y.[Yu], Shen, X.Y.[Xin-Yong], Xing, L.[Lizhu], Che, H.Z.[Hui-Zheng],
Global Aerosol Classification Based on Aerosol Robotic Network (AERONET) and Satellite Observation,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Ma, H., Liang, S., Shi, H., Zhang, Y.,
An Optimization Approach for Estimating Multiple Land Surface and Atmospheric Variables From the Geostationary Advanced Himawari Imager Top-of-Atmosphere Observations,
GeoRS(59), No. 4, April 2021, pp. 2888-2908.
IEEE DOI 2104
Land surface, Atmospheric modeling, Clouds, Soil, MODIS, Advanced Himawari imager (AHI), remote sensing BibRef

Choi, W.[Wonei], Lee, H.[Hanlim], Kim, D.W.[Dae-Won], Kim, S.[Serin],
Improving Spatial Coverage of Satellite Aerosol Classification Using a Random Forest Model,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Lin, T.H.[Tang-Huang], Tsay, S.C.[Si-Chee], Lien, W.H.[Wei-Hung], Lin, N.H.[Neng-Huei], Hsiao, T.C.[Ta-Chih],
Spectral Derivatives of Optical Depth for Partitioning Aerosol Type and Loading,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Robles, J.[José], Zamorano, J.[Jaime], Pascual, S.[Sergio], de Miguel, A.S.[Alejandro Sánchez], Gallego, J.[Jesús], Gaston, K.J.[Kevin J.],
Evolution of Brightness and Color of the Night Sky in Madrid,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Burgués, J.[Javier], Esclapez, M.D.[María Deseada], Doñate, S.[Silvia], Pastor, L.[Laura], Marco, S.[Santiago],
Aerial Mapping of Odorous Gases in a Wastewater Treatment Plant Using a Small Drone,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Calassou, G.[Gabriel], Foucher, P.Y.[Pierre-Yves], Léon, J.F.[Jean-François],
Industrial Plume Properties Retrieved by Optimal Estimation Using Combined Hyperspectral and Sentinel-2 Data,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Boselli, A.[Antonella], Sannino, A.[Alessia], d'Emilio, M.[Mariagrazia], Wang, X.[Xuan], Amoruso, S.[Salvatore],
Aerosol Characterization during the Summer 2017 Huge Fire Event on Mount Vesuvius (Italy) by Remote Sensing and In Situ Observations,
RS(13), No. 10, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Yu, Z.Q.[Zhong-Qi], Qu, Y.H.[Yuan-Hao], Wang, Y.X.[Yun-Xin], Ma, J.H.[Jing-Hui], Cao, Y.[Yu],
Application of Machine-Learning-Based Fusion Model in Visibility Forecast: A Case Study of Shanghai, China,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Choi, W.[Wonei], Kang, H.W.[Hyeong-Woo], Shin, D.H.[Dong-Ho], Lee, H.[Hanlim],
Satellite-Based Aerosol Classification for Capital Cities in Asia Using a Random Forest Model,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Rao, L.[Lanlan], Xu, J.[Jian], Efremenko, D.S.[Dmitry S.], Loyola, D.G.[Diego G.], Doicu, A.[Adrian],
Optimization of Aerosol Model Selection for TROPOMI/S5P,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Ou, Y.[Yang], Li, L.[Lei], Li, Z.Q.[Zheng-Qiang], Zhang, Y.[Ying], Dubovik, O.[Oleg], Derimian, Y.[Yevgeny], Chen, C.[Cheng], Fuertes, D.[David], Xie, Y.S.[Yi-Song], Lopatin, A.[Anton], Ducos, F.[Fabrice], Peng, Z.[Zongren],
Spatio-Temporal Variability of Aerosol Components, Their Optical and Microphysical Properties over North China during Winter Haze in 2012, as Derived from POLDER/PARASOL Satellite Observations,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef
And: Correction: RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Zeng, Z.L.[Zhao-Liang], Wang, Z.[Zemin], Zhang, B.[Baojun],
An Adjustment Approach for Aerosol Optical Depth Inferred from CALIPSO,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Zhang, L.[Luo], Liu, P.[Peng], Wang, L.[Lizhe], Liu, J.B.[Jian-Bo], Song, B.Z.[Bing-Ze], Zhang, Y.W.[Yu-Wei], He, G.J.[Guo-Jin], Zhang, H.[Hui],
Improved 1-km-Resolution Hourly Estimates of Aerosol Optical Depth Using Conditional Generative Adversarial Networks,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Lin, H.[Hao], Li, S.W.[Si-Wei], Xing, J.[Jia], Yang, J.[Jie], Wang, Q.X.[Qing-Xin], Dong, L.[Lechao], Zeng, X.Y.[Xiao-Yue],
Fusing Retrievals of High Resolution Aerosol Optical Depth from Landsat-8 and Sentinel-2 Observations over Urban Areas,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Guan, J.[Jian], Jin, B.[Bohan], Ding, Y.Z.[Yi-Zhe], Wang, W.[Wen], Li, G.X.[Guo-Xiang], Ciren, P.[Pubu],
Global Surface HCHO Distribution Derived from Satellite Observations with Neural Networks Technique,
RS(13), No. 20, 2021, pp. xx-yy.
DOI Link 2110
Formaldehyde. HCHO. BibRef

Jin, C.L.[Chun-Lin], Xue, Y.[Yong], Jiang, X.X.[Xing-Xing], Sun, Y.X.[Yu-Xin], Wu, S.H.[Shu-Hui],
Improved Bi-Angle Aerosol Optical Depth Retrieval Algorithm from AHI Data Based on Particle Swarm Optimization,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Leckey, J.P.[John P.], Damadeo, R.[Robert], Hill, C.A.[Charles A.],
Stratospheric Aerosol and Gas Experiment (SAGE) from SAGE III on the ISS to a Free Flying SAGE IV Cubesat,
RS(13), No. 22, 2021, pp. xx-yy.
DOI Link 2112
BibRef

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Shi, C.[Chong], Hashimoto, M.[Makiko], Shiomi, K.[Kei], Nakajima, T.[Teruyuki],
Development of an Algorithm to Retrieve Aerosol Optical Properties Over Water Using an Artificial Neural Network Radiative Transfer Scheme: First Result From GOSAT-2/CAI-2,
GeoRS(59), No. 12, December 2021, pp. 9861-9872.
IEEE DOI 2112
Aerosols, Atmospheric modeling, Sea measurements, Water, Satellites, Estimation, Atmospheric measurements, Aerosols, neural network, remote sensing BibRef

Zheng, L.M.[Lian-Ming], Lin, R.[Rui], Wang, X.M.[Xue-Mei], Chen, W.H.[Wei-Hua],
The Development and Application of Machine Learning in Atmospheric Environment Studies,
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Xia, X.H.[Xing-Hui], Zhao, B.[Bin], Zhang, T.H.[Tian-Hao], Wang, L.[Luyao], Gu, Y.[Yu], Liou, K.N.[Kuo-Nan], Mao, F.Y.[Fei-Yue], Liu, B.M.[Bo-Ming], Bo, Y.C.[Yan-Chen], Huang, Y.[Yusi], Dong, J.[Jiadan], Gong, W.[Wei], Zhu, Z.M.[Zhong-Min],
Satellite-Derived Aerosol Optical Depth Fusion Combining Active and Passive Remote Sensing Based on Bayesian Maximum Entropy,
GeoRS(60), 2022, pp. 1-13.
IEEE DOI 2112
Aerosols, Cloud computing, Sensors, Satellites, MODIS, Spatiotemporal phenomena, Remote sensing, Active-passive fusion, Moderate Resolution Imaging Spectroradiometer (MODIS) BibRef

Chang, C.W.[Chiao-Wei], Chen, W.T.[Wei-Ting], Chen, Y.C.[Yi-Chun],
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Jha, S.S.[Sudhanshu Shekhar], Nidamanuri, R.R.[Rama Rao], Ientilucci, E.J.[Emmett J.],
Influence of atmospheric modeling on spectral target detection through forward modeling approach in multi-platform remote sensing data,
PandRS(183), 2022, pp. 286-306.
Elsevier DOI 2201
Target detection, Radiative transfer, Aerosol optical thickness, Atmospheric profiles, Multi-platform dataset BibRef

Kang, Y.[Yoojin], Kim, M.[Miae], Kang, E.[Eunjin], Cho, D.J.[Dong-Jin], Im, J.[Jungho],
Improved retrievals of aerosol optical depth and fine mode fraction from GOCI geostationary satellite data using machine learning over East Asia,
PandRS(183), 2022, pp. 253-268.
Elsevier DOI 2201
Aerosol optical depth, Fine mode fraction, Geostationary Ocean Color Imager, Machine learning, Shapley Additive exPlanations values BibRef

Grzegorski, M.[Michael], Poli, G.[Gabriele], Cacciari, A.[Alessandra], Jafariserajehlou, S.[Soheila], Holdak, A.[Andriy], Lang, R.[Ruediger], Vazquez-Navarro, M.[Margarita], Munro, R.[Rosemary], Fougnie, B.[Bertrand],
Multi-Sensor Retrieval of Aerosol Optical Properties for Near-Real-Time Applications Using the Metop Series of Satellites: Concept, Detailed Description, and First Validation,
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Wei, S.W.[Shih-Wei], Lu, C.H.(.[Cheng-Hsuan (Sarah)], Johnson, B.T.[Benjamin T.], Dang, C.[Cheng], Stegmann, P.[Patrick], Grogan, D.[Dustin], Ge, G.Q.[Guo-Qing], Hu, M.[Ming],
The Influence of Aerosols on Satellite Infrared Radiance Simulations and Jacobians: Numerical Experiments of CRTM and GSI,
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DOI Link 2202
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Tong, Y.C.[Yi-Cheng], Chen, S.[Sijie], Xiao, D.[Da], Zhang, K.[Kai], Fang, J.[Jing], Liu, C.[Chong], Shen, Y.B.[Yi-Bing], Liu, D.[Dong],
Lidar Ratio Regional Transfer Method for Extinction Coefficient Accuracy Improvement in Lidar Networks,
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Lidar for aerosol analysis. BibRef

Ou, Y.[Yang], Li, Z.Q.[Zheng-Qiang], Chen, C.[Cheng], Zhang, Y.[Ying], Li, K.[Kaitao], Shi, Z.[Zheng], Dong, J.T.[Jian-Tao], Xu, H.[Hua], Peng, Z.[Zongren], Xie, Y.S.[Yi-Song], Luo, J.[Jie],
Evaluation of MERRA-2 Aerosol Optical and Component Properties over China Using SONET and PARASOL/GRASP Data,
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Sun, J.[Jie], Ding, K.[Kaihua], Lai, Z.L.[Zu-Long], Huang, H.J.[Hai-Jun],
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Chen, X.F.[Xing-Feng], Zhao, L.M.[Li-Min], Zheng, F.J.[Feng-Jie], Li, J.G.[Jia-Guo], Li, L.[Lei], Ding, H.[Haonan], Zhang, K.N.[Kai-Nan], Liu, S.[Shumin], Li, D.H.[Dong-Hui], de Leeuw, G.[Gerrit],
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Popp, T.[Thomas], Mittaz, J.P.D.[Jonathan P.D.],
Systematic Propagation of AVHRR AOD Uncertainties: A Case Study to Demonstrate the FIDUCEO Approach,
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Fajardo-Zambrano, C.M.[Carlos Mario], Bravo-Aranda, J.A.[Juan Antonio], Granados-Muñoz, M.J.[María José], Montilla-Rosero, E.[Elena], Casquero-Vera, J.A.[Juan Andrés], Rejano, F.[Fernando], Castillo, S.[Sonia], Alados-Arboledas, L.[Lucas],
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She, L.[Lu], Zhang, H.K.[Hankui K.], Bu, Z.Q.[Zi-Qiang], Shi, Y.[Yun], Yang, L.[Lu], Zhao, J.T.[Jin-Tao],
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Lee, S.[Seunghee], Kim, G.[Ganghan], Lee, M.I.[Myong-In], Choi, Y.H.[Yong-Han], Song, C.K.[Chang-Keun], Kim, H.K.[Hyeon-Kook],
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Wang, P.D.[Pei-Dong], Holloway, T.[Tracey], Bindl, M.[Matilyn], Harkey, M.[Monica], de Smedt, I.[Isabelle],
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Keppens, A.[Arno], Compernolle, S.[Steven], Hubert, D.[Daan], Verhoelst, T.[Tijl], Granville, J.[José], Lambert, J.C.[Jean-Christopher],
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Su, Y.Y.[Yue-Yuan], Han, Y.[Yong], Luo, H.[Hao], Zhang, Y.[Yuan], Shao, S.Y.[Shi-Yong], Xie, X.X.[Xin-Xin],
Physical-Optical Properties of Marine Aerosols over the South China Sea: Shipboard Measurements and MERRA-2 Reanalysis,
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Li, W.T.[Wei-Tao], Su, X.[Xin], Feng, L.[Lan], Wu, J.Y.[Jin-Yang], Zhang, Y.J.[Yu-Jie], Cao, M.D.[Meng-Dan],
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Chen, Y.L.[Yuan-Lin], Fan, M.[Meng], Li, M.Y.[Ming-Yang], Li, Z.B.[Zhong-Bin], Tao, J.H.[Jin-Hua], Wang, Z.B.[Zhi-Bao], Chen, L.[Liangfu],
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Han, J.[Jie], Wu, J.J.[Jia-Ji], Zhang, L.J.[Li-Jun], Wang, H.G.[Hong-Guang], Zhu, Q.L.[Qing-Lin], Zhang, C.[Chao], Zhao, H.[Hui], Zhang, S.B.[Shou-Bao],
A Classifying-Inversion Method of Offshore Atmospheric Duct Parameters Using AIS Data Based on Artificial Intelligence,
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Freitas, A.D.[Arthur Dias], Fornaro, A.[Adalgiza],
Atmospheric Formaldehyde Monitored by TROPOMI Satellite Instrument throughout 2020 over Sao Paulo State, Brazil,
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Falah, S.[Somaya], Mhawish, A.[Alaa], Omar, A.H.[Ali H.], Sorek-Hamer, M.[Meytar], Lyapustin, A.I.[Alexei I.], Banerjee, T.[Tirthankar], Kizel, F.[Fadi], Broday, D.M.[David M.],
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Phillips, M.C.[Mark C.], Bernacki, B.E.[Bruce E.], Conry, P.T.[Patrick T.], Brown, M.J.[Michael J.],
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Ge, B.Y.[Bang-Yu], Li, Z.Q.[Zheng-Qiang], Chen, C.[Cheng], Hou, W.Z.[Wei-Zhen], Xie, Y.S.[Yi-Song], Zhu, S.[Sifeng], Qie, L.[Lili], Zhang, Y.[Ying], Li, K.[Kaitao], Xu, H.[Hua], Ma, Y.[Yan], Yan, L.[Lei], Mei, X.D.[Xiao-Dong],
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Tang, F.Y.[Fu-Ying], Wang, W.H.[Wei-He], Si, F.Q.[Fu-Qi], Zhou, H.J.[Hai-Jin], Luo, Y.H.[Yu-Han], Qian, Y.Y.[Yuan-Yuan],
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Li, S.Q.[Shu-Qun], Hu, H.[Hao], Fang, C.G.[Cheng-Gege], Wang, S.C.[Si-Chen], Xun, S.P.[Shang-Pei], He, B.F.[Bin-Fang], Wu, W.Y.[Wen-Yu], Huo, Y.F.[Yan-Feng],
Hyperspectral Infrared Atmospheric Sounder (HIRAS) Atmospheric Sounding System,
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Sun, Y.Q.[Yue-Qiang], Wang, B.[Bowen], Meng, X.G.[Xiang-Guang], Tang, X.C.[Xin-Chun], Yan, F.[Feng], Zhang, X.G.[Xian-Guo], Bai, W.H.[Wei-Hua], Du, Q.F.[Qi-Fei], Wang, X.[Xianyi], Cai, Y.R.[Yue-Rong], Guo, B.[Bibo], Wei, S.L.[Shi-Long], Qiao, H.[Hao], Hu, P.[Peng], Li, Y.P.[Yong-Ping], Wang, X.Y.[Xin-Yue],
Analysis of Orbital Atmospheric Density from QQ-Satellite Precision Orbits Based on GNSS Observations,
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Fang, L.[Li], Hasekamp, O.[Otto], Fu, G.L.[Guang-Liang], Gong, W.S.[Wei-Shu], Wang, S.P.[Shu-Peng], Wang, W.H.[Wei-He], Han, Q.J.[Qi-Jin], Tang, S.H.[Shi-Hao],
Retrieval of Aerosol Optical Properties over Land Using an Optimized Retrieval Algorithm Based on the Directional Polarimetric Camera,
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DOI Link 2209
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Li, H.[Hui], Liu, B.M.[Bo-Ming], Ma, X.[Xin], Ma, Y.Y.[Ying-Ying], Jin, S.K.[Shi-Kuan], Fan, R.N.[Ruo-Nan], Wang, W.[Weiyan], Fang, J.[Jing], Zhao, Y.F.[Yue-Feng], Gong, W.[Wei],
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Jiang, X.X.[Xing-Xing], Xue, Y.[Yong], Jin, C.L.[Chun-Lin], Bai, R.[Rui], Sun, Y.X.[Yu-Xin], Wu, S.H.[Shu-Hui],
A Simple Band Ratio Library (BRL) Algorithm for Retrieval of Hourly Aerosol Optical Depth Using FY-4A AGRI Geostationary Satellite Data,
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DOI Link 2210
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Bai, J.Y.[Jing-Yu], Bai, L.[Lu], Li, J.L.[Jin-Lu], Wang, Y.K.[Yan-Kun], Xie, J.Y.[Jin-Yu], Zhang, D.[Danmeng], Guo, L.X.[Li-Xin],
Sensitivity Analysis of 1,3-Butadiene Monitoring Based on Space-Based Detection in the Infrared Band,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
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Yu, X.Y.[Xin-Yu], Nichol, J.[Janet], Lee, K.H.[Kwon Ho], Li, J.[Jing], Wong, M.S.[Man Sing],
Analysis of Long-Term Aerosol Optical Properties Combining AERONET Sunphotometer and Satellite-Based Observations in Hong Kong,
RS(14), No. 20, 2022, pp. xx-yy.
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Ma, Q.H.[Qi-Han], Liu, Y.Y.[Ying-Ying], Qiu, T.[Ting], Huang, T.X.[Ting-Xuan], Deng, T.[Tao], Hu, Z.Y.[Zhi-Yuan], Cui, T.W.[Ting-Wei],
Satellite-Observed Four-Dimensional Spatiotemporal Characteristics of Maritime Aerosol Types over the Coastal Waters of the Guangdong-Hong Kong-Macao Greater Bay Area and the Northern South China Sea,
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Ding, H.N.[Hao-Nan], Zhao, L.M.[Li-Min], Liu, S.W.[Shan-Wei], Chen, X.F.[Xing-Feng], de Leeuw, G.[Gerrit], Wang, F.[Fu], Zheng, F.J.[Feng-Jie], Zhang, Y.[Yuhuan], Liu, J.[Jun], Li, J.G.[Jia-Guo], She, L.[Lu], Si, Y.[Yidan], Gu, X.F.[Xing-Fa],
FY-4A/AGRI Aerosol Optical Depth Retrieval Capability Test and Validation Based on NNAeroG,
RS(14), No. 21, 2022, pp. xx-yy.
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Han, Y.Y.[Yuan-Yuan], Xie, F.[Fei], Cui, F.[Fei], Wang, F.[Feiyang], Li, X.[Xin], Feng, W.[Wuhu],
Extreme Change Events of Stratospheric HCl and N2O in the Mid-Latitude Region of the Northern Hemisphere,
RS(14), No. 23, 2022, pp. xx-yy.
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Xiao, X.J.[Xian-Jun], Weng, F.Z.[Fu-Zhong],
A Comparison of Information Content at Microwave to Millimeter Wave Bands for Atmospheric Sounding,
RS(14), No. 23, 2022, pp. xx-yy.
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Shevtsov, B.M.[Boris M.], Perezhogin, A.N.[Andrey N.], Seredkin, I.N.[Ilya N.],
Atmospheric Optical Characteristics in the Area of 30-400 km,
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Belikovich, M.V.[Mikhail V.], Makarov, D.S.[Dmitriy S.], Serov, E.A.[Evgeny A.], Kulikov, M.Y.[Mikhail Yu.], Feigin, A.M.[Alexander M.],
Validation of Atmospheric Absorption Models within the 20-60 GHz Band by Simultaneous Radiosonde and Microwave Observations: The Advantage of Using ECS Formalism,
RS(14), No. 23, 2022, pp. xx-yy.
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Gu, H.R.[Hao-Ran], Zhang, Y.[Yuhuan], Fan, C.[Cheng], Li, Z.Q.[Zheng-Qiang], Hou, W.Z.[Wei-Zhen], Liu, Z.H.[Zhen-Hai], Xie, Y.S.[Yi-Song], Xu, H.[Hua], Zhang, L.[Luo], Ma, J.[Jinji],
A Comprehensive Analysis of Ultraviolet Remote Sensing for Aerosol Layer Height Retrieval from Multi-Angle Polarization Satellite Measurements,
RS(14), No. 24, 2022, pp. xx-yy.
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Liu, N.[Nana], Cui, S.C.[Sheng-Cheng], Luo, T.[Tao], Chen, S.P.[Shun-Ping], Yang, K.X.[Kai-Xuan], Ma, X.B.[Xue-Bin], Sun, G.[Gang], Li, X.B.[Xue-Bin],
Characteristics of Aerosol Extinction Hygroscopic Growth in the Typical Coastal City of Qingdao, China,
RS(14), No. 24, 2022, pp. xx-yy.
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Pan, Y.F.[Yu-Feng], Zhao, J.B.[Jin-Biao], Lu, P.[Ping], Sima, C.T.[Chao-Tan], Liu, D.M.[De-Ming],
Recent Advances in Light-Induced Thermoelastic Spectroscopy for Gas Sensing: A Review,
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Javed, S.[Sadaf], Shahzad, M.I.[Muhammad Imran], Abbas, S.[Sawaid], Nazeer, M.[Majid],
Long-Term Variability of Atmospheric Visual Range (1980-2020) over Diverse Topography of Pakistan,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Fan, Y.Z.[Yi-Zhe], Sun, X.B.[Xia-Bing], Ti, R.[Rufang], Huang, H.L.[Hong-Lian], Liu, X.[Xiao], Yu, H.X.[Hai-Xiao],
Aerosol Retrieval Study from a Particulate Observing Scanning Polarimeter Onboard Gao-Fen 5B without Prior Surface Knowledge, Based on the Optimal Estimation Method,
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DOI Link 2301
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Barnet, C.D.[Chris D.], Smith, N.[Nadia], Ide, K.[Kayo], Garrett, K.[Kevin], Jones, E.[Erin],
Evaluating the Value of CrIS Shortwave-Infrared Channels in Atmospheric-Sounding Retrievals,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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Zang, Z.L.[Zeng-Liang], Bao, X.[Xulun], Li, Y.[Yi], Qu, Y.M.[You-Ming], Niu, D.[Dan], Liu, N.[Ning], Chen, X.[Xisong],
A Modified RNN-Based Deep Learning Method for Prediction of Atmospheric Visibility,
RS(15), No. 3, 2023, pp. xx-yy.
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Tao, S.C.[Si-Chen], Sun, Z.C.[Zong-Chen], Lin, X.[Xingwen], Zhang, Z.Z.[Zhen-Zhen], Wu, C.F.[Chao-Fan], Zhang, Z.Y.[Zhao-Yang], Zhou, B.Z.[Ben-Zhi], Zhao, Z.[Zhen], Cao, C.C.[Chen-Chen], Guan, X.Y.[Xin-Yu], Zhuang, Q.J.[Qian-Jin], Wen, Q.Q.[Qing-Qing], Xu, Y.L.[Yu-Ling],
Negative Air Ion (NAI) Dynamics over Zhejiang Province, China, Based on Multivariate Remote Sensing Products,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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Wang, Y.X.[Yu-Xuan], Sun, X.B.[Xia-Bing], Huang, H.L.[Hong-Lian], Ti, R.[Rufang], Liu, X.[Xiao], Fan, Y.Z.[Yi-Zhe],
Study on Influencing Factors of the Information Content of Satellite Remote-Sensing Aerosol Vertical Profiles Using Oxygen A-Band,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Li, S.[Sheng], Liu, Y.[Yanna], Du, K.[Ke],
Quantifying Emissions from Fugitive Area Sources Using a Hybrid Method of Multi-Path Optical Remote Sensing and Tomographic Inverse-Dispersion Techniques,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
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Huang, C.[Congwu], Niu, T.[Tao], Wu, H.[Hao], Qu, Y.[Yawei], Wang, T.[Tijian], Li, M.M.[Meng-Meng], Li, R.[Rong], Liu, H.L.[Hong-Li],
A Data Assimilation Method Combined with Machine Learning and Its Application to Anthropogenic Emission Adjustment in CMAQ,
RS(15), No. 6, 2023, pp. 1711.
DOI Link 2304
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Lemmouchi, F.[Farouk], Cuesta, J.[Juan], Lachatre, M.[Mathieu], Brajard, J.[Julien], Coman, A.[Adriana], Beekmann, M.[Matthias], Derognat, C.[Claude],
Machine Learning-Based Improvement of Aerosol Optical Depth from CHIMERE Simulations Using MODIS Satellite Observations,
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Scarlatti, F.[Francesco], Gómez-Amo, J.L.[José L.], Valdelomar, P.C.[Pedro C.], Estellés, V.[Víctor], Utrillas, M.P.[María Pilar],
A Machine Learning Approach to Derive Aerosol Properties from All-Sky Camera Imagery,
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Demeyer, S.[Séverine], Kristoffersen, S.K.[Samuel K.], Le Pichon, A.[Alexis], Larsonnier, F.[Franck], Fischer, N.[Nicolas],
Contribution to Uncertainty Propagation Associated with On-Site Calibration of Infrasound Monitoring Systems,
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Spatial-Temporal Fusion of 10-Min Aerosol Optical Depth Products with the GEO-LEO Satellite Joint Observations,
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White, E.[Evan], Shephard, M.W.[Mark W.], Cady-Pereira, K.E.[Karen E.], Kharol, S.K.[Shailesh K.], Ford, S.[Sean], Dammers, E.[Enrico], Chow, E.[Evan], Thiessen, N.[Nikolai], Tobin, D.[David], Quinn, G.[Greg], O'Brien, J.[Jason], Bash, J.[Jesse],
Accounting for Non-Detects: Application to Satellite Ammonia Observations,
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Shah, S.S.A.[Syed Shakeel Ahmad], Huang, Z.W.[Zhong-Wei], ul Haq, E.[Ehtiram], Alam, K.[Khan], and Its Relationship with Meteorology over the
Exploring the Spatiotemporal Variation in Light-Absorbing AerosolsH Hindukush-Himalaya-Karakoram Region,
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Long, Z.Y.[Zhi-Yong], Jin, Z.[Zichun], Meng, Y.Z.[Yi-Zhen], Ma, J.[Jin],
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Li, H.[Han], Gu, M.J.[Ming-Jian], Zhang, C.M.[Chun-Ming], Xie, M.Z.[Meng-Zhen], Yang, T.H.[Tian-Hang], Hu, Y.[Yong],
Retrieving Atmospheric Gas Profiles Using FY-3E/HIRAS-II Infrared Hyperspectral Data by Neural Network Approach,
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Koushafar, M.[Mohammad], Sohn, G.[Gunho], Gordon, M.[Mark],
Deep Convolutional Neural Network for Plume Rise Measurements in Industrial Environments,
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Kokhanovsky, A.A.[Alexander A.], Brell, M.[Maximillian], Segl, K.[Karl], Bianchini, G.[Giovanni], Lanconelli, C.[Christian], Lupi, A.[Angelo], Petkov, B.[Boyan], Picard, G.[Ghislain], Arnaud, L.[Laurent], Stone, R.S.[Robert S.], Chabrillat, S.[Sabine],
First Retrievals of Surface and Atmospheric Properties Using EnMAP Measurements over Antarctica,
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The Detection of Desert Aerosol Incorporating Coherent Doppler Wind Lidar and Rayleigh-Mie-Raman Lidar,
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Aerosol Optical Depth Measurements from a Simulated Low-Cost Multi-Wavelength Ground-Based Camera: A Clear Case over a Peri-Urban Area,
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DOI Link 2401
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Zhou, D.[Dong], Wang, Q.X.[Qing-Xin], Li, S.W.[Si-Wei], Yang, J.[Jie],
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Song, Y.Y.[Yu-Yang], He, Y.[Yang], Leng, H.Z.[Hong-Ze],
Analysis of Atmospheric Elements in Near Space Based on Meteorological-Rocket Soundings over the East China Sea,
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DOI Link 2402
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Zhou, X.Z.[Xing-Zhao], Chen, B.[Bin], Ye, Q.[Qia], Zhao, L.[Lin], Song, Z.H.[Zhi-Hao], Wang, Y.X.[Yi-Xuan], Hu, J.[Jiashun], Chen, R.[Ruming],
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Xu, G.R.[Gui-Rong],
A Review of Remote Sensing of Atmospheric Profiles and Cloud Properties by Ground-Based Microwave Radiometers in Central China,
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A Machine Learning Approach to Retrieving Aerosol Optical Depth Using Solar Radiation Measurements,
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Chen, Q.X.[Qi-Xiang], Huang, C.L.[Chun-Lin], Dong, S.K.[Shi-Kui], Lin, K.F.[Kai-Feng],
Satellite-Based Background Aerosol Optical Depth Determination via Global Statistical Analysis of Multiple Lognormal Distribution,
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DOI Link 2404
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Zhang, L.P.[Li-Ping], Wang, X.F.[Xu-Feng], Huang, G.H.[Guang-Hui], Zhang, S.L.[Song-Lin],
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DeLand, M.T.[Matthew T.], Kowalewski, M.G.[Matthew G.], Colarco, P.R.[Peter R.], Ramos-Izquierdo, L.[Luis],
The ARGOS Instrument for Stratospheric Aerosol Measurements,
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DOI Link 2405
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Dong, J.[Jiadan], Zhang, T.H.[Tian-Hao], Wang, L.[Lunche], Li, Z.Q.[Zheng-Qiang], Wong, M.S.[Man Sing], Bilal, M.[Muhammad], Zhu, Z.M.[Zhong-Min], Mao, F.Y.[Fei-Yue], Xia, X.[Xinghui], Han, G.[Ge], Xu, Q.Q.[Qiang-Qiang], Gu, Y.[Yu], Lin, Y.[Yun], Zhao, B.[Bin], Li, Z.W.[Zhi-Wei], Xu, K.[Kai], Chen, X.L.[Xiao-Ling], Gong, W.[Wei],
First retrieval of daily 160 m aerosol optical depth over urban areas using Gaofen-1/6 synergistic observations: Algorithm development and validation,
PandRS(211), 2024, pp. 372-391.
Elsevier DOI 2405
Daily 160 m AOD dataset, Retrieval algorithm, Gaofen-1/6 WFV, High resolution LSR modeling, Urban areas BibRef

Kauppi, A.[Anu], Kukkurainen, A.[Antti], Lipponen, A.[Antti], Laine, M.[Marko], Arola, A.[Antti], Lindqvist, H.[Hannakaisa], Tamminen, J.[Johanna],
A Bayesian Framework to Quantify Uncertainty in Aerosol Optical Model Selection Applied to TROPOMI Measurements,
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Dabove, P.[Paolo], Bagheri, M.[Milad],
Enhancing Atmospheric Monitoring Capabilities: A Comparison of Low- and High-Cost GNSS Networks for Tropospheric Estimations,
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Wang, L.[Lunche], Su, X.[Xin], Wang, Y.[Yi], Cao, M.[Mengdan], Lang, Q.[Qin], Li, H.P.[Hua-Ping], Sun, J.[Junyao], Zhang, M.[Ming], Qin, W.[Wenmin], Li, L.[Lei], Yang, L.[Leiku],
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PandRS(214), 2024, pp. 261-281.
Elsevier DOI 2407
Aerosol optical depth, Surface reflectance, Fine mode fraction, Fine mode AOD, Satellite remote sensing BibRef

Oladipo, B.[Bolaji], Gomes, J.[Joseph], McGill, M.[Matthew], Selmer, P.[Patrick],
Leveraging Deep Learning as a New Approach to Layer Detection and Cloud-Aerosol Classification Using ICESat-2 Atmospheric Data,
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Su, X.[Xin], Huang, G.[Ge], Wang, L.[Lin], Wei, Y.F.[Yi-Feng], Ma, X.Y.[Xiao-Yu], Wang, L.[Lunche], Feng, L.[Lan],
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DOI Link 2409
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Wang, H.Y.[Hao-Yue], Lu, Y.H.[Yue-Hua], Yu, K.[Ke], Xiao, F.H.[Fei-Hong], Guo, R.Z.[Rong-Zhi], Yan, N.C.[Nai-Cong], Wang, W.G.[Wei-Guo],
Comparative Study on the Vertical Column Concentration Inversion Algorithm of Tropospheric Trace Gas Based on the MAX-DOAS Measurement Spectrum,
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Ren, Y.J.[Yi-Jie], Chen, B.L.[Bing-Long], Bu, L.B.[Ling-Bing], Hu, G.[Gen], Fang, J.Y.[Jing-Yi], Liyanage, P.[Pasindu],
The First Validation of Aerosol Optical Parameters Retrieved from the Terrestrial Ecosystem Carbon Inventory Satellite (TECIS) and Its Application,
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DOI Link 2410
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DOI Link 2501
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Chen, J.[Jing], Duan, J.[Jing], Yang, L.[Ling], Chen, Y.[Yong], Guo, L.J.[Li-Jun], Cai, J.[Juan],
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Zhu, J.M.[Jing-Miao], Qiao, C.C.[Cong-Cong], Duan, M.Z.[Min-Zheng],
Retrieving Aerosol Optical Depth over Land from Landsat-8 Satellite Images with the Aid of Cloud Shadows,
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Giant Aerosol Observations with Cloud Radar: Methodology and Effects,
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Evaluation of ICESat-2 ATL09 Atmospheric Products Using CALIOP and MODIS Space-Based Observations,
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Du, B.[Bailin], Zhong, B.[Bo], Cai, H.[He], Wu, S.L.[Shan-Long], Qiao, Y.[Yang], Wang, X.Y.[Xiao-Ya], Yang, A.[Aixia], Wu, J.J.[Jun-Jun], Liu, Q.H.[Qin-Huo], Jiang, J.X.[Jin-Xiong], Zhang, H.Z.[Hai-Zhen],
Improving AOD Algorithm Evaluation: A Spatial Matching Method for Minimizing Quality Control Bias,
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Zheng, S.Y.[Si-Yue], Chen, Y.R.[Yan-Rong], Eziz, A.[Anwar], Kurban, A.[Alishir], van de Voorde, T.[Tim], de Maeyer, P.[Philippe],
Machine-Learning-Based Monitoring of Night Sky Brightness Using Sky Quality Meters and Multi-Source Remote Sensing,
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Li, Q.H.[Qing-Hao], Ge, J.M.[Jin-Ming], Li, Y.Z.[Yi-Ze], Mu, Q.Y.[Qing-Yu], Peng, N.[Nan], Su, J.[Jing], Wang, B.[Bo], Zhang, C.[Chi], Liu, B.C.[Bo-Chun],
Unraveling Aerosol and Low-Level Cloud Interactions Under Multi-Factor Constraints at the Semi-Arid Climate and Environment Observatory of Lanzhou University,
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Ou, Z.L.[Zhuo-Liang], Zhong, J.H.[Jia-Hao], Hao, Y.Q.[Yong-Qiang], Li, R.X.[Ruo-Xi], Wan, X.[Xin], Wang, K.[Kang], Chen, J.[Jiawen], Han, H.[Hao], Song, X.Y.[Xing-Yan], Du, W.Y.[Wen-Yu], Tang, Y.Y.[Yan-Yan],
Near-Real-Time Global Thermospheric Density Variations Unveiled by Starlink Ephemeris,
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Hopkins, D.[Daniel], Yang, L.[Le], Clare, R.[Richard],
On Feed-Forward Neural-Network-Based Atmospheric Tomography,
IVCNZ24(1-6)
IEEE DOI 2503
Adaptation models, Atmospheric modeling, Computational modeling, Tomography, Optical imaging, Adaptive optics, Polynomials, Zernike polynomials BibRef

Giganti, A.[Antonio], Mandelli, S.[Sara], Bestagini, P.[Paolo], Marcon, M.[Marco], Tubaro, S.[Stefano],
Super-Resolution of BVOC Maps by Adapting Deep Learning Methods,
ICIP23(1650-1654)
IEEE DOI 2312
Biogenic Volatile Organic Compounds. BibRef

Mukherjee, R.[Ryan], Rollend, D.[Derek], Christie, G.[Gordon], Hadzic, A.[Armin], Matson, S.[Sally], Saksena, A.[Anshu], Hughes, M.[Marisa],
Towards Indirect Top-Down Road Transport Emissions Estimation,
EarthVision21(1092-1101)
IEEE DOI 2109
Training, Climate change, Visualization, Satellites, Uncertainty, Roads, Estimation BibRef

Calassou, G., Foucher, P.Y., Leon, J.F.,
Aerosol Plumes Characterization By Hyperspectral Images Coupled With Sentinel-2 Products,
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Mechtley, B.[Brandon], Roberts, C.[Christopher], Stein, J.[Julian], Nandin, B.[Benjamin], Sha, X.W.[Xin Wei],
Enactive Steering of an Experiential Model of the Atmosphere,
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Yoshida, T., Wasenmüller, O., Stricker, D.,
Time-of-flight sensor depth enhancement for automotive exhaust gas,
ICIP17(1955-1959)
IEEE DOI 1803
Automotive engineering, Gaussian distribution, Gaussian mixture model, Mathematical model, Solids, Standards, image processing BibRef

Luffarelli, M., Govaerts, Y., Goossens, C., Wolters, E.L.A., Swinnen, E.,
Joint retrieval of surface reflectance and aerosol properties from PROBA-V observations, part I: Algorithm performance evaluation,
MultiTemp17(1-6)
IEEE DOI 1712
BibRef
And: A4, A5, A1, A3, A2:
Joint Surface Reflectance and AeRosol properties retrieval in the PV-LAC framework, part II: Validation,
MultiTemp17(1-4)
IEEE DOI 1712
aerosols, PROBA-V observations, aerosol properties, algorithm performance evaluation, atmospheric state variables, joint retrieval. aerosols, atmospheric optics, AOT observations, Aerosol Optical Thickness, validation BibRef

Eu, K.S.[Kok Seng], Yap, K.M.[Kian Meng], Tan, W.C.[Wan Chew],
A Simulation Study of Micro-Drone Chemical Plume Tracking Performance in Tree Farm Environments,
IVIC17(260-269).
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BibRef

Lin, T.H.[Tang-Huang], Liu, G.R.[Gin-Rong], Liu, C.Y.[Chian-Yi],
A Novel Index For Atmospheric Aerosol Types Categorization With Spectral Optical Depths From Satellite Retrieval,
ISPRS16(B8: 277-279).
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Marek, L., Campbell, M., Epton, M., Storer, M., Kingham, S.,
Real-time Environmental Sensors To Improve Health In The Sensing City,
ISPRS16(B2: 729-733).
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Levis, A.[Aviad], Schechner, Y.Y.[Yoav Y.], Davis, A.B.,
Multiple-Scattering Microphysics Tomography,
CVPR17(5797-5806)
IEEE DOI 1711
Atmospheric modeling, Clouds, Computational modeling, Mathematical model, Scattering, Tomography BibRef

Levis, A.[Aviad], Schechner, Y.Y.[Yoav Y.], Aides, A.[Amit], Davis, A.B.,
Airborne Three-Dimensional Cloud Tomography,
ICCV15(3379-3387)
IEEE DOI 1602
Atmospheric modeling BibRef

Veikherman, D.[Dmitry], Aides, A.[Amit], Schechner, Y.Y.[Yoav Y.], Levis, A.[Aviad],
Clouds in the Cloud,
ACCV14(IV: 659-674).
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Light-field imaging for spaceborne instruments. Monitor the atmosphere. BibRef

Rajitha, K., Mohan, M.M.P.[M.M. Prakash], Varma, M.R.R.,
Effect of cirrus cloud on normalized difference Vegetation Index (NDVI) and Aerosol Free Vegetation Index (AFRI): A study based on LANDSAT 8 images,
ICAPR15(1-5)
IEEE DOI 1511
aerosols BibRef

Julien, Y., Sobrino, J.A.,
CloudSim: A fair benchmark for comparison of methods for times series reconstruction from cloud and atmospheric contamination,
MultiTemp15(1-4)
IEEE DOI 1511
clouds BibRef

Bhattacharjee, S., Ghosh, S.K.,
Exploring spatial dependency of meteorological attributes for multivariate analysis: A granger causality test approach,
ICAPR15(1-6)
IEEE DOI 1511
atmospheric humidity BibRef

Chapter on Remote Sensing General Issue, Land Use, Land Cover continues in
Air Quality, Air Pollution, Aerosols, General Pollution .

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