What is he best known for?
The fields of study he is best known for:
Robert O. Green mainly investigates Remote sensing, Imaging spectrometer, Endmember, Vegetation and Airborne visible/infrared imaging spectrometer.
His Remote sensing research incorporates elements of Spectrometer and Water vapor.
His work in Imaging spectrometer tackles topics such as Radiance which are related to areas like Electromagnetic spectrum, Radiometry and Field of view.
His Endmember research focuses on Snow and how it connects with Image resolution and Wavelength.
His Vegetation research integrates issues from Albedo and Pixel.
His Airborne visible/infrared imaging spectrometer research is multidisciplinary, incorporating perspectives in Mixture model, Chaparral and Model selection.
His most cited work include:
- Imaging Spectroscopy and the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) (1315 citations)
- Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models (1000 citations)
- Mapping Chaparral in the Santa Monica Mountains Using Multiple Endmember Spectral Mixture Models (1000 citations)
What are the main themes of his work throughout his whole career to date?
Robert O. Green spends much of his time researching Remote sensing, Imaging spectrometer, Imaging spectroscopy, Spectrometer and Optics.
His biological study spans a wide range of topics, including Snow, Airborne visible/infrared imaging spectrometer and Atmospheric correction.
His Snow study combines topics from a wide range of disciplines, such as Vegetation, Endmember, Wavelength and Grain size.
His work on Endmember is being expanded to include thematically relevant topics such as Chaparral.
His Imaging spectrometer research also works with subjects such as
- Detector that intertwine with fields like Spectral bands,
- Mixture model most often made with reference to Pixel.
In his study, Remote sensing is strongly linked to Methane, which falls under the umbrella field of Spectrometer.
He most often published in these fields:
- Remote sensing (65.03%)
- Imaging spectrometer (43.17%)
- Imaging spectroscopy (24.59%)
What were the highlights of his more recent work (between 2017-2021)?
- Remote sensing (65.03%)
- Imaging spectroscopy (24.59%)
- Imaging spectrometer (43.17%)
In recent papers he was focusing on the following fields of study:
The scientist’s investigation covers issues in Remote sensing, Imaging spectroscopy, Imaging spectrometer, Spectrometer and Hyperspectral imaging.
His Remote sensing research incorporates themes from Snow, Airborne visible/infrared imaging spectrometer and Aerosol.
His Imaging spectroscopy study integrates concerns from other disciplines, such as Radiative transfer, Atmospheric models, Water vapor and Radiance.
Imaging spectrometer is a subfield of Optics that Robert O. Green tackles.
He combines subjects such as Visible infrared and Detector with his study of Spectrometer.
His Hyperspectral imaging research includes themes of Copernicus, Algorithm and Satellite, Satellite imaging.
Between 2017 and 2021, his most popular works were:
- California's methane super-emitters. (40 citations)
- Optimal estimation for imaging spectrometer atmospheric correction (38 citations)
- Imaging spectrometer stray spectral response: In-flight characterization, correction, and validation (23 citations)
In his most recent research, the most cited papers focused on:
His primary areas of study are Remote sensing, Spectrometer, Imaging spectroscopy, Imaging spectrometer and Airborne visible/infrared imaging spectrometer.
Robert O. Green studies Hyperspectral imaging, a branch of Remote sensing.
His research integrates issues of Remote sensing, Visible infrared and Satellite, Satellite imaging in his study of Spectrometer.
His studies in Imaging spectroscopy integrate themes in fields like Radiative transfer and Infrared.
His Imaging spectrometer research includes elements of Atmospheric correction and Methane.
Robert O. Green has researched Airborne visible/infrared imaging spectrometer in several fields, including Mineral dust and Reflectivity.
This overview was generated by a machine learning system which analysed the scientist’s
body of work. If you have any feedback, you can
contact us
here.
