Kamu erişimi zorunlu olan makaleler - Alexei LyapustinDaha fazla bilgi edinin
Hiçbir yerde sunulmuyor: 8
Full-coverage high-resolution daily PM2. 5 estimation using MAIAC AOD in the Yangtze River Delta of China
Q Xiao, Y Wang, HH Chang, X Meng, G Geng, A Lyapustin, Y Liu
Remote Sensing of Environment 199, 437-446, 2017
Zorunlu olanlar: US National Aeronautics and Space Administration
Consistency of vegetation index seasonality across the Amazon rainforest
EE Maeda, YM Moura, F Wagner, T Hilker, AI Lyapustin, Y Wang, J Chave, ...
International Journal of Applied Earth Observation and Geoinformation 52, 42-53, 2016
Zorunlu olanlar: Academy of Finland
Estimating daily PM2. 5 concentrations in New York City at the neighborhood-scale: Implications for integrating non-regulatory measurements
K Huang, J Bi, X Meng, G Geng, A Lyapustin, KJ Lane, D Gu, PL Kinney, ...
Science of The Total Environment 697, 134094, 2019
Zorunlu olanlar: US National Aeronautics and Space Administration
Impact of aerosol layering, complex aerosol mixing, and cloud coverage on high-resolution MAIAC aerosol optical depth measurements: Fusion of lidar, AERONET, satellite, and …
I Rogozovsky, A Ansmann, D Althausen, B Heese, R Engelmann, J Hofer, ...
Atmospheric Environment 247, 118163, 2021
Zorunlu olanlar: Federal Ministry of Education and Research, Germany
Vector radiative transfer code SORD: Performance analysis and quick start guide
S Korkin, A Lyapustin, A Sinyuk, B Holben, A Kokhanovsky
Journal of Quantitative Spectroscopy and Radiative Transfer 200, 295-310, 2017
Zorunlu olanlar: US National Aeronautics and Space Administration
Evaluating impacts of snow, surface water, soil and vegetation on empirical vegetation and snow indices for the Utqiaġvik tundra ecosystem in Alaska with the LVS3 model
Q Zhang, T Yao, KF Huemmrich, EM Middleton, A Lyapustin, Y Wang
Remote Sensing of Environment 240, 111677, 2020
Zorunlu olanlar: US National Aeronautics and Space Administration
An API for spaceborne sub-meter resolution products for earth science
CSR Neigh, ML Carroll, PM Montesano, DA Slayback, MR Wooten, ...
IGARSS 2019-2019 IEEE International Geoscience and Remote Sensing Symposium …, 2019
Zorunlu olanlar: US National Aeronautics and Space Administration
Preliminary fAPARchl products from MODIS and hyperion
Q Zhang, T Yao, EM Middleton, AI Lyapustin, Y Wang
2016 IEEE International Geoscience and Remote Sensing Symposium (IGARSS …, 2016
Zorunlu olanlar: US National Aeronautics and Space Administration
Bir yerde sunuluyor: 106
Global estimates of fine particulate matter using a combined geophysical-statistical method with information from satellites, models, and monitors
A Van Donkelaar, RV Martin, M Brauer, NC Hsu, RA Kahn, RC Levy, ...
Environmental science & technology 50 (7), 3762-3772, 2016
Zorunlu olanlar: US National Aeronautics and Space Administration, Natural Sciences and …
Advancements in the Aerosol Robotic Network (AERONET) Version 3 database–automated near-real-time quality control algorithm with improved cloud screening for Sun photometer …
DM Giles, A Sinyuk, MG Sorokin, JS Schafer, A Smirnov, I Slutsker, TF Eck, ...
Atmospheric Measurement Techniques 12 (1), 169-209, 2019
Zorunlu olanlar: US National Aeronautics and Space Administration
MODIS collection 6 MAIAC algorithm
A Lyapustin, Y Wang, S Korkin, D Huang
Atmospheric Measurement Techniques 11 (10), 5741-5765, 2018
Zorunlu olanlar: US National Aeronautics and Space Administration
Reconstructing 1-km-resolution high-quality PM2. 5 data records from 2000 to 2018 in China: spatiotemporal variations and policy implications
J Wei, Z Li, A Lyapustin, L Sun, Y Peng, W Xue, T Su, M Cribb
Remote Sensing of Environment 252, 112136, 2021
Zorunlu olanlar: National Natural Science Foundation of China
Global estimates and long-term trends of fine particulate matter concentrations (1998–2018)
MS Hammer, A van Donkelaar, C Li, A Lyapustin, AM Sayer, NC Hsu, ...
Environmental Science & Technology 54 (13), 7879-7890, 2020
Zorunlu olanlar: US National Oceanic and Atmospheric Administration, Natural Sciences and …
Assessing PM2.5 Exposures with High Spatiotemporal Resolution across the Continental United States
Q Di, I Kloog, P Koutrakis, A Lyapustin, Y Wang, J Schwartz
Environmental science & technology 50 (9), 4712-4721, 2016
Zorunlu olanlar: US National Institutes of Health
Monthly global estimates of fine particulate matter and their uncertainty
A Van Donkelaar, MS Hammer, L Bindle, M Brauer, JR Brook, MJ Garay, ...
Environmental Science & Technology 55 (22), 15287-15300, 2021
Zorunlu olanlar: US National Aeronautics and Space Administration
Improved 1 km resolution PM2.5 estimates across China using enhanced space–time extremely randomized trees
J Wei, Z Li, M Cribb, W Huang, W Xue, L Sun, J Guo, Y Peng, J Li, ...
Atmospheric Chemistry and Physics 20 (6), 3273-3289, 2020
Zorunlu olanlar: US National Science Foundation, National Natural Science Foundation of China
Photosynthetic seasonality of global tropical forests constrained by hydroclimate
K Guan, M Pan, H Li, A Wolf, J Wu, D Medvigy, KK Caylor, J Sheffield, ...
Nature Geoscience 8 (4), 284-289, 2015
Zorunlu olanlar: US Department of Energy, US National Aeronautics and Space Administration
Spatial validation reveals poor predictive performance of large-scale ecological mapping models
P Ploton, F Mortier, M Réjou-Méchain, N Barbier, N Picard, V Rossi, ...
Nature communications 11 (1), 4540, 2020
Zorunlu olanlar: European Commission, Agence Nationale de la Recherche
Fifty years of Landsat science and impacts
MA Wulder, DP Roy, VC Radeloff, TR Loveland, MC Anderson, ...
Remote Sensing of Environment 280, 113195, 2022
Zorunlu olanlar: US National Oceanic and Atmospheric Administration
Estimation of daily PM10 and PM2. 5 concentrations in Italy, 2013–2015, using a spatiotemporal land-use random-forest model
M Stafoggia, T Bellander, S Bucci, M Davoli, K De Hoogh, F De'Donato, ...
Environment international 124, 170-179, 2019
Zorunlu olanlar: Government of Italy
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