What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Ecosystem
His primary areas of investigation include Remote sensing, Lidar, Vegetation, Canopy and Forest management.
His Remote sensing research is mostly focused on the topic Remote sensing.
His Lidar research is multidisciplinary, incorporating perspectives in Basal area, Sampling, Hydrology, Regression analysis and Algorithm.
The study incorporates disciplines such as Active fire, Soil water and Stage in addition to Vegetation.
As part of the same scientific family, Andrew T. Hudak usually focuses on Canopy, concentrating on Leaf area index and intersecting with Inversion, Atmospheric sciences, Diameter at breast height, Edaphic and Western Hemlock.
Andrew T. Hudak interconnects Natural resource, Natural resource management and Resource management in the investigation of issues within Forest management.
His most cited work include:
- Remote sensing techniques to assess active fire characteristics and post-fire effects (596 citations)
- Nearest neighbor imputation of species-level, plot-scale forest structure attributes from LiDAR data (313 citations)
- Integration of lidar and Landsat ETM+ data for estimating and mapping forest canopy height (277 citations)
What are the main themes of his work throughout his whole career to date?
His main research concerns Remote sensing, Lidar, Vegetation, Ecology and Forestry.
Crown is closely connected to Tree in his research, which is encompassed under the umbrella topic of Remote sensing.
The various areas that Andrew T. Hudak examines in his Lidar study include Forest management, Forest inventory, Sampling and Basal area.
He has researched Vegetation in several fields, including Hydrology, Canopy and Physical geography.
His work carried out in the field of Canopy brings together such families of science as Atmospheric sciences and Litter.
His Fire regime research integrates issues from Boreal and Meteorology.
He most often published in these fields:
- Remote sensing (39.55%)
- Lidar (31.82%)
- Vegetation (25.91%)
What were the highlights of his more recent work (between 2018-2021)?
- Ecosystem (15.00%)
- Remote sensing (39.55%)
- Forestry (18.18%)
In recent papers he was focusing on the following fields of study:
Andrew T. Hudak focuses on Ecosystem, Remote sensing, Forestry, Vegetation and Fire regime.
His Ecosystem research incorporates themes from Biomass, Climate change and Land management.
His study of Lidar is a part of Remote sensing.
His Lidar research includes themes of Forest management, Canopy, Temperate coniferous forest and Remote sensing.
His Forestry research incorporates elements of Ecological succession and Precipitation.
His Fire regime study integrates concerns from other disciplines, such as Species richness, Physical geography and Prescribed burn.
Between 2018 and 2021, his most popular works were:
- The Fire and Smoke Model Evaluation Experiment-A Plan for Integrated, Large Fire-Atmosphere Field Campaigns. (25 citations)
- Examining post-fire vegetation recovery with Landsat time series analysis in three western North American forest types (16 citations)
- Fire Behaviour and Smoke Modelling: Model Improvement and Measurement Needs for Next-generation Smoke Research and Forecasting Systems (11 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Ecosystem
The scientist’s investigation covers issues in Ecosystem, Prescribed burn, Fire behavior, Species diversity and Species richness.
Andrew T. Hudak works mostly in the field of Ecosystem, limiting it down to concerns involving Forestry and, occasionally, Shrubland, Biodiversity, Steppe and Biomass.
His biological study spans a wide range of topics, including Environmental planning, Meteorology, Smoke and Sustainability.
His research integrates issues of Graminoid, Seedling, Vegetation and Introduced species in his study of Species richness.
His research in Fire regime focuses on subjects like Taiga, which are connected to Remote sensing.
His Remote sensing research is multidisciplinary, incorporating elements of Physical geography and Time series.
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