What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Optics
The scientist’s investigation covers issues in Remote sensing, Albedo, Bidirectional reflectance distribution function, Radiometry and Moderate-resolution imaging spectroradiometer.
The various areas that Philip Lewis examines in his Remote sensing study include Pixel, Atmospheric correction, Canopy, Meteorology and Radiative transfer.
His work in Albedo addresses subjects such as Spectral bands, which are connected to disciplines such as Temperate climate and Spectroradiometer.
He performs multidisciplinary study in the fields of Bidirectional reflectance distribution function and Land cover via his papers.
His Radiometry study combines topics in areas such as Remote sensing, Data set and Understory.
His research integrates issues of Change detection, Multispectral pattern recognition and Algorithm in his study of Moderate-resolution imaging spectroradiometer.
His most cited work include:
- First operational BRDF, albedo nadir reflectance products from MODIS (1631 citations)
- The Moderate Resolution Imaging Spectroradiometer (MODIS): land remote sensing for global change research (1084 citations)
- Prototyping a global algorithm for systematic fire-affected area mapping using MODIS time series data (417 citations)
What are the main themes of his work throughout his whole career to date?
Philip Lewis mainly investigates Remote sensing, Bidirectional reflectance distribution function, Albedo, Earth observation and Canopy.
His Remote sensing study incorporates themes from Vegetation, Radiative transfer, Meteorology and Reflectivity.
His Vegetation research is multidisciplinary, incorporating perspectives in Range, Ecosystem and Leaf area index.
The concepts of his Bidirectional reflectance distribution function study are interwoven with issues in Pixel, Atmospheric correction and Moderate-resolution imaging spectroradiometer.
His work deals with themes such as Image resolution and Nadir, which intersect with Albedo.
His studies deal with areas such as Remote sensing, Scattering, Hyperspectral imaging and Radiometry as well as Canopy.
He most often published in these fields:
- Remote sensing (58.10%)
- Bidirectional reflectance distribution function (18.18%)
- Albedo (13.83%)
What were the highlights of his more recent work (between 2015-2021)?
- Remote sensing (58.10%)
- Earth observation (13.04%)
- Radiative transfer (12.25%)
In recent papers he was focusing on the following fields of study:
Philip Lewis mostly deals with Remote sensing, Earth observation, Radiative transfer, Data assimilation and Atmospheric sciences.
Philip Lewis has included themes like Albedo, Bidirectional reflectance distribution function and Ray tracing in his Remote sensing study.
His Earth observation study deals with Parametric statistics intersecting with Nonparametric regression.
The Radiative transfer study combines topics in areas such as Thermal, Leaf area index, Tree, Molecular physics and Lidar.
His Data assimilation research is multidisciplinary, relying on both Hyperspectral imaging, Winter wheat and Reflectivity.
His work in Atmospheric sciences tackles topics such as Biosphere model which are related to areas like Assimilation, Primary production, Boreal, Eddy covariance and Carbon cycle.
Between 2015 and 2021, his most popular works were:
- A general method to normalize Landsat reflectance data to nadir BRDF adjusted reflectance (130 citations)
- Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods (91 citations)
- Quantifying Vegetation Biophysical Variables from Imaging Spectroscopy Data: A Review on Retrieval Methods (91 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Optics
His primary areas of study are Remote sensing, Earth observation, Neuroscience, Data stream and Data stream mining.
His research on Remote sensing focuses in particular on Canopy reflectance.
His Earth observation study combines topics in areas such as Agriculture, Food security, Range and Bayes' theorem.
His work on Neuropsychiatry, Neuromodulation, Optogenetics and Transcranial magnetic stimulation as part of general Neuroscience study is frequently connected to Human health, therefore bridging the gap between diverse disciplines of science and establishing a new relationship between them.
His Data stream study combines topics from a wide range of disciplines, such as Data mining, Parametric statistics, Imaging spectroscopy, Multicollinearity and Regression.
His Data stream mining research incorporates elements of Spectroradiometer and Nonparametric regression.
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