What is he best known for?
The fields of study he is best known for:
- Statistics
- Meteorology
- Optics
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.
His most cited work include:
- Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors (473 citations)
- Global Estimates of Fine Particulate Matter Using a Combined Geophysical-Statistical Method with Information from Satellites, Models, and Monitors (473 citations)
- Hyperspectral remote sensing of foliar nitrogen content. (286 citations)
What are the main themes of his work throughout his whole career to date?
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.
He most often published in these fields:
- Remote sensing (63.18%)
- Atmospheric correction (41.09%)
- Aerosol (36.82%)
What were the highlights of his more recent work (between 2019-2021)?
- Aerosol (36.82%)
- Atmospheric sciences (24.81%)
- Remote sensing (63.18%)
In recent papers he was focusing on the following fields of study:
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.
Between 2019 and 2021, his most popular works were:
- Improved 1 km resolution PM 2.5 estimates across China using enhanced space–time extremely randomized trees (58 citations)
- Spatial validation reveals poor predictive performance of large-scale ecological mapping models. (36 citations)
- Global Estimates and Long-Term Trends of Fine Particulate Matter Concentrations (1998-2018). (31 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Optics
- Meteorology
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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