What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Ecosystem
Vegetation, Greenhouse gas, Meteorology, Biomass and Remote sensing are his primary areas of study.
His research in Vegetation intersects with topics in Land use, Physical geography and Pollution.
His work in Meteorology addresses subjects such as Land cover, which are connected to disciplines such as Vegetation type and Vegetation types.
His Biomass research is multidisciplinary, incorporating elements of Fire regime, Atmospheric sciences and Carbon cycle.
His Carbon cycle research is multidisciplinary, incorporating perspectives in Shrubland, Woodland and Taiga.
His studies in Remote sensing integrate themes in fields like Image resolution, Logging, Coherence and Interferometry.
His most cited work include:
- Vegetation burning in the year 2000: Global burned area estimates from SPOT VEGETATION data (206 citations)
- A new, global, multi‐annual (2000–2007) burnt area product at 1 km resolution (195 citations)
- Restoration Ecology of Lowland Tropical Peatlands in Southeast Asia: Current Knowledge and Future Research Directions (164 citations)
What are the main themes of his work throughout his whole career to date?
Kevin Tansey spends much of his time researching Remote sensing, Vegetation, Lidar, Greenhouse gas and Synthetic aperture radar.
His work deals with themes such as Cartography and Pixel, which intersect with Remote sensing.
His research integrates issues of Hydrology, Climate change, Meteorology and Atmospheric sciences in his study of Vegetation.
His Meteorology research incorporates themes from Land cover and Physical geography.
His studies deal with areas such as Peat, Biomass and Carbon cycle as well as Greenhouse gas.
The Synthetic aperture radar study combines topics in areas such as Radar, Interferometry, C band and Taiga.
He most often published in these fields:
- Remote sensing (48.33%)
- Vegetation (31.67%)
- Lidar (12.50%)
What were the highlights of his more recent work (between 2018-2021)?
- Vegetation (31.67%)
- Remote sensing (48.33%)
- Normalized Difference Vegetation Index (8.33%)
In recent papers he was focusing on the following fields of study:
Kevin Tansey mainly focuses on Vegetation, Remote sensing, Normalized Difference Vegetation Index, Radiometer and Moderate-resolution imaging spectroradiometer.
His biological study spans a wide range of topics, including Condition index, Spatial distribution and Leaf area index.
His Remote sensing research focuses on Digital elevation model in particular.
In his study, which falls under the umbrella issue of Digital elevation model, Lidar is strongly linked to Old-growth forest.
His Normalized Difference Vegetation Index research includes themes of National park, Woody cover, Estimation and Phenology.
His Moderate-resolution imaging spectroradiometer research incorporates elements of Tropics, Atmospheric sciences, Field and Precipitation.
Between 2018 and 2021, his most popular works were:
- Agricultural drought monitoring using European Space Agency Sentinel 3A land surface temperature and normalized difference vegetation index imageries (23 citations)
- Forest biomass retrieval approaches from earth observation in different biomes (23 citations)
- Land Surface Temperature Retrieval from Sentinel-3A Sea and Land Surface Temperature Radiometer, Using a Split-Window Algorithm (12 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Artificial intelligence
- Ecosystem
His primary areas of study are Remote sensing, Radiometer, Vegetation, Normalized Difference Vegetation Index and Spatial distribution.
Kevin Tansey studies Remote sensing, focusing on Digital elevation model in particular.
As part of one scientific family, Kevin Tansey deals mainly with the area of Digital elevation model, narrowing it down to issues related to the Tropical vegetation, and often Lidar.
His Vegetation research incorporates elements of Agriculture, Radiance, Precipitation, Condition index and Moderate-resolution imaging spectroradiometer.
His research integrates issues of Image resolution, Advanced very-high-resolution radiometer and Field in his study of Normalized Difference Vegetation Index.
His biological study spans a wide range of topics, including Woodland, Physical geography, Biome and Scale.
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