What is he best known for?
The fields of study he is best known for:
- Optics
- Remote sensing
- Ecology
His main research concerns Remote sensing, Canopy, Chlorophyll, Hyperspectral imaging and Leaf area index.
His Remote sensing study combines topics in areas such as Photochemical Reflectance Index, Chlorophyll fluorescence and Imaging spectrometer.
His research in Canopy intersects with topics in Primary production, Transect, Vegetation, Normalized Difference Vegetation Index and Spectral bands.
His Chlorophyll research includes elements of Tree canopy and Chlorophyll a.
His Hyperspectral imaging research integrates issues from Image resolution, Pixel and Radiative transfer.
His Leaf area index research is multidisciplinary, incorporating elements of Precision agriculture, Thematic Mapper, Sky and Solar zenith angle.
His most cited work include:
- Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture (1297 citations)
- Hyperspectral vegetation indices and novel algorithms for predicting green LAI of crop canopies: Modeling and validation in the context of precision agriculture (1297 citations)
- Integrated narrow-band vegetation indices for prediction of crop chlorophyll content for application to precision agriculture (1091 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Remote sensing, Hyperspectral imaging, Canopy, Leaf area index and Vegetation.
His research integrates issues of Precision agriculture, Chlorophyll and Imaging spectrometer in his study of Remote sensing.
John R. Miller has included themes like Growing season, Photochemical Reflectance Index, Normalized Difference Vegetation Index, Chlorophyll content and Radiative transfer in his Hyperspectral imaging study.
His study in Canopy is interdisciplinary in nature, drawing from both Image resolution, Bidirectional reflectance distribution function and Zenith.
His studies in Leaf area index integrate themes in fields like Algorithm, Solar zenith angle, Thematic Mapper and Black spruce.
His work deals with themes such as Boreal, Transect, Crown and Taiga, which intersect with Vegetation.
He most often published in these fields:
- Remote sensing (78.69%)
- Hyperspectral imaging (28.96%)
- Canopy (27.87%)
What were the highlights of his more recent work (between 2006-2019)?
- Remote sensing (78.69%)
- Hyperspectral imaging (28.96%)
- Vegetation (19.67%)
In recent papers he was focusing on the following fields of study:
John R. Miller spends much of his time researching Remote sensing, Hyperspectral imaging, Vegetation, Leaf area index and Lidar.
He interconnects Growing season, Bidirectional reflectance distribution function, Canopy, Photochemical Reflectance Index and Radiative transfer in the investigation of issues within Remote sensing.
The Hyperspectral imaging study combines topics in areas such as Precision agriculture, Chlorophyll, Black spruce, Pixel and Shadow.
His research in Precision agriculture tackles topics such as Normalized Difference Vegetation Index which are related to areas like Row crop.
The concepts of his Vegetation study are interwoven with issues in Spectral bands, Seasonality and Taiga.
Within one scientific family, John R. Miller focuses on topics pertaining to Point cloud under Leaf area index, and may sometimes address concerns connected to Thresholding and Atmospheric radiative transfer codes.
Between 2006 and 2019, his most popular works were:
- Imaging chlorophyll fluorescence with an airborne narrow-band multispectral camera for vegetation stress detection (199 citations)
- Assessing Canopy PRI for Water Stress detection with Diurnal Airborne Imagery (189 citations)
- Comparative study between a new nonlinear model and common linear model for analysing laboratory simulated-forest hyperspectral data (181 citations)
In his most recent research, the most cited papers focused on:
- Optics
- Ecology
- Remote sensing
John R. Miller focuses on Remote sensing, Vegetation, Hyperspectral imaging, Leaf area index and Canopy.
His Remote sensing research incorporates elements of Photochemical Reflectance Index, Chlorophyll, Chlorophyll fluorescence, Chlorophyll a and Radiative transfer.
The study incorporates disciplines such as Atmospheric correction, Precision agriculture and Radiometry in addition to Chlorophyll.
He combines subjects such as Tree, Lidar, Olive trees and Nadir with his study of Vegetation.
His Leaf area index study integrates concerns from other disciplines, such as Growing season, Photosynthetically active radiation, Soil texture, Cover crop and Thematic Mapper.
His research on Canopy often connects related topics like Bidirectional reflectance distribution function.
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