His primary areas of investigation include Vegetation, Remote sensing, Lidar, Satellite imagery and Land cover. John Armston has researched Vegetation in several fields, including Biomass, Forest management, Hydrology, Backscatter and Digital elevation model. His study of Thematic Mapper is a part of Remote sensing.
His study focuses on the intersection of Lidar and fields such as Canopy with connections in the field of Leaf area index. His Satellite imagery research includes elements of Bank, Linear model, Linear regression and Generalized linear model. As a part of the same scientific family, John Armston mostly works in the field of Mean squared error, focusing on Tropics and, on occasion, Forest inventory.
John Armston mainly focuses on Remote sensing, Lidar, Vegetation, Canopy and Biomass. The concepts of his Remote sensing study are interwoven with issues in Mean squared error and Leaf area index. His biological study spans a wide range of topics, including Global ecosystem and Calibration.
His work carried out in the field of Vegetation brings together such families of science as Land cover, Synthetic aperture radar, Hydrology, Bank and Woodland. In his study, Regression analysis is inextricably linked to Range, which falls within the broad field of Canopy. His Biomass research is multidisciplinary, incorporating elements of Ecosystem and Atmospheric sciences.
John Armston mostly deals with Lidar, Remote sensing, Canopy, Biogeosciences and Aboveground biomass. He interconnects Range, Global ecosystem, Calibration and Vegetation in the investigation of issues within Lidar. His Calibration course of study focuses on Zenith and Leaf area index.
His Vegetation study also includes fields such as
The scientist’s investigation covers issues in Lidar, Remote sensing, Canopy, Biomass and Global ecosystem. The Lidar study combines topics in areas such as Aboveground biomass, Leaf area index, Environmental resource management and Laser scanning. His research in Remote sensing is mostly concerned with Remote sensing.
His Canopy research incorporates themes from Climate change mitigation, Forest ecology, Ecosystem, Scale and Renewable energy. His work in Biomass covers topics such as Physical geography which are related to areas like Vegetation type and Temperate forest. His Global ecosystem study incorporates themes from Estimator, Meteorology, Forest dynamics and Tree canopy.
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.
An integrated pan‐tropical biomass map using multiple reference datasets
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Global Change Biology (2016)
Nondestructive estimates of above‐ground biomass using terrestrial laser scanning
Kim Calders;Glenn Newnham;Andrew Burt;Simon Murphy.
Methods in Ecology and Evolution (2015)
An Evaluation of the ALOS PALSAR L-Band Backscatter—Above Ground Biomass Relationship Queensland, Australia: Impacts of Surface Moisture Condition and Vegetation Structure
Richard Lucas;John Armston;Russell Fairfax;Rod Fensham.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (2010)
Prediction and validation of foliage projective cover from Landsat-5 TM and Landsat-7 ETM+ imagery.
John David Armston;Robert J. Denham;Tim J. Danaher;Peter F. Scarth.
Journal of Applied Remote Sensing (2009)
Terrestrial Laser Scanning for Plot-Scale Forest Measurement
Glenn J. Newnham;John D. Armston;Kim Calders;Kim Calders;Mathias I. Disney.
Current Forestry Reports , 1 (4) pp. 239-251. (2015) (2015)
Integration of LiDAR and QuickBird imagery for mapping riparian biophysical parameters and land cover types in Australian tropical savannas
Lara A. Arroyo;Kasper Johansen;John Armston;Stuart Phinn.
Forest Ecology and Management (2010)
Multi-resolution time series imagery for forest disturbance and regrowth monitoring in Queensland, Australia
Michael Schmidt;Richard Lucas;Peter Bunting;Jan Verbesselt.
Remote Sensing of Environment (2015)
Integration of radar and Landsat-derived foliage projected cover for woody regrowth mapping, Queensland, Australia
Richard M. Lucas;Natasha Cronin;Mahta Moghaddam;Alex Lee.
Remote Sensing of Environment (2006)
Direct retrieval of canopy gap probability using airborne waveform lidar
John Armston;M. Disney;Philip Lewis;Peter Scarth.
Remote Sensing of Environment (2013)
The Global Ecosystem Dynamics Investigation: High-resolution laser ranging of the Earth’s forests and topography
Ralph Dubayah;James Bryan Blair;Scott Goetz;Lola Fatoyinbo.
Science of Remote Sensing. 1: 100002. (2020)
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