Alexei Lyapustin mainly investigates Remote sensing, Atmospheric correction, Aerosol, Meteorology and Vegetation. His studies deal with areas such as Cross-validation, AERONET, Photochemical Reflectance Index, Moderate-resolution imaging spectroradiometer and Mixed model as well as Remote sensing. His AERONET research focuses on Sun photometer and how it relates to Mineral dust, Photometer and Scale.
His Atmospheric correction study integrates concerns from other disciplines, such as Elevation, Algorithm, Radiative transfer and Missing data. His work focuses on many connections between Aerosol and other disciplines, such as Bidirectional reflectance distribution function, that overlap with his field of interest in Spectroradiometer, Subpixel rendering, Mathematical model, Real-time locating system and Inversion. His studies in Meteorology integrate themes in fields like Advanced very-high-resolution radiometer and Time series.
Alexei Lyapustin mostly deals with Remote sensing, Atmospheric correction, Aerosol, Atmospheric sciences and Meteorology. His work deals with themes such as Albedo, Snow, Vegetation, Moderate-resolution imaging spectroradiometer and Radiative transfer, which intersect with Remote sensing. His Atmospheric correction research includes elements of Climatology, Bidirectional reflectance distribution function, Spatial variability, Algorithm and Atmospheric radiative transfer codes.
Alexei Lyapustin combines subjects such as Cloud cover, Water vapor and Air quality index with his study of Aerosol. Alexei Lyapustin usually deals with Atmospheric sciences and limits it to topics linked to Particulates and Air pollution. The study incorporates disciplines such as Sun photometer and Radiometer in addition to AERONET.
His primary areas of investigation include Aerosol, Atmospheric sciences, Remote sensing, Atmospheric correction and AERONET. His Aerosol research entails a greater understanding of Meteorology. His study in Atmospheric sciences is interdisciplinary in nature, drawing from both Particulates, Fine particulate and Geographically Weighted Regression.
His study connects Geostationary orbit and Remote sensing. He interconnects Water vapor and Moderate-resolution imaging spectroradiometer in the investigation of issues within Atmospheric correction. His work deals with themes such as Angstrom exponent, Single-scattering albedo, Optical depth and Climate model, which intersect with AERONET.
His main research concerns Aerosol, Atmospheric sciences, Remote sensing, Air pollution and Fine particulate. His Aerosol research is mostly focused on the topic Single-scattering albedo. His work in Remote sensing covers topics such as AERONET which are related to areas like Radiance.
His Air pollution study combines topics in areas such as Gradient boosting, Atmospheric correction, Coefficient of determination and Moderate-resolution imaging spectroradiometer. The study incorporates disciplines such as Image resolution, Climatology, Resolution, Pollution and Atmospheric model in addition to Moderate-resolution imaging spectroradiometer. His research integrates issues of Chemical transport model and Geographically Weighted Regression in his study of Fine particulate.
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Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors
Aaron Van Donkelaar;Randall V. Martin;Randall V. Martin;Michael Brauer;N. Christina Hsu.
Environmental Science & Technology (2016)
Advancements in the Aerosol Robotic Network (AERONET) Version 3 database – automated near-real-time quality control algorithm with improved cloud screening for Sun photometer aerosol optical depth (AOD) measurements
David M. Giles;Alexander Sinyuk;Mikhail G. Sorokin;Joel S. Schafer.
Atmospheric Measurement Techniques (2019)
Multiangle implementation of atmospheric correction (MAIAC): 2. Aerosol algorithm
A. Lyapustin;A. Lyapustin;Y. Wang;Y. Wang;I. Laszlo;R. Kahn.
Journal of Geophysical Research (2011)
Hyperspectral remote sensing of foliar nitrogen content.
Yuri Knyazikhin;Mitchell A. Schull;Pauline Stenberg;Matti Mõttus.
Proceedings of the National Academy of Sciences of the United States of America (2013)
MODIS Collection 6 MAIAC Algorithm
Alexei Lyapustin;Yujie Wang;Sergey Korkin;Dong Huang.
Atmospheric Measurement Techniques (2018)
Assessing PM2.5 Exposures with High Spatiotemporal Resolution across the Continental United States.
Qian Di;Itai Kloog;Petros Koutrakis;Alexei Lyapustin.
Environmental Science & Technology (2016)
Photosynthetic seasonality of global tropical forests constrained by hydroclimate
Kaiyu Guan;Kaiyu Guan;Ming Pan;Haibin Li;Adam Wolf.
Nature Geoscience (2015)
Vegetation dynamics and rainfall sensitivity of the Amazon
Thomas Hilker;Alexei I. Lyapustin;Compton J. Tucker;Forrest G. Hall;Forrest G. Hall.
Proceedings of the National Academy of Sciences of the United States of America (2014)
Estimating Ground-Level PM(sub 2.5) Concentrations in the Southeastern United States Using MAIAC AOD Retrievals and a Two-Stage Model
Xuefei Hu;Lance A. Waller;Alexei Lyapustin;Yujie Wang;Yujie Wang.
Remote Sensing of Environment (2014)
A New Hybrid Spatio-temporal Model for Estimating Daily Multi-year PM2.5 Concentrations Across Northeastern USA Using High Resolution Aerosol Optical Depth Data
Itai Kloog;Alexandra A. Chudnovsky;Allan C. Just;Francesco Nordio.
Atmospheric Environment (2014)
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