What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Biodiversity
Erkki Tomppo mainly focuses on Remote sensing, Forest inventory, National forest inventory, Forestry and National forest.
His Remote sensing research is multidisciplinary, incorporating elements of Pixel, Nonparametric statistics and Tree.
His biological study spans a wide range of topics, including Statistics, Plot and Field plot.
His National forest inventory research is multidisciplinary, incorporating perspectives in Multi-source and Pinus radiata.
He combines subjects such as Sampling, Data mining and Satellite imagery with his study of Forestry.
His National forest study integrates concerns from other disciplines, such as Forest resource, Forest ecology and Bark.
His most cited work include:
- Estimating carbon accumulation rates of undrained mires in Finland–application to boreal and subarctic regions: (609 citations)
- Remote sensing support for national forest inventories (273 citations)
- Combining national forest inventory field plots and remote sensing data for forest databases (221 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Remote sensing, Forest inventory, Environmental resource management, National forest inventory and Forestry.
His studies examine the connections between Remote sensing and genetics, as well as such issues in Pixel, with regards to Thematic Mapper.
His Forest inventory research includes themes of Sampling, Statistics, Kyoto Protocol and Small area estimation.
His Environmental resource management study combines topics from a wide range of disciplines, such as Multi-source, Biodiversity, United Nations Framework Convention on Climate Change, National forest and Greenhouse gas.
His studies deal with areas such as Forest resource, Forest biodiversity and Convention on Biological Diversity as well as National forest.
His study on National forest inventory is mostly dedicated to connecting different topics, such as Field plot.
He most often published in these fields:
- Remote sensing (28.30%)
- Forest inventory (24.53%)
- Environmental resource management (19.81%)
What were the highlights of his more recent work (between 2010-2021)?
- Remote sensing (28.30%)
- Greenhouse gas (6.60%)
- Statistics (9.43%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Remote sensing, Greenhouse gas, Statistics, Sampling and National forest.
Remote sensing is frequently linked to Snow in his study.
His Greenhouse gas research incorporates elements of Atmospheric sciences, Environmental resource management, Biomass, Energy policy and Fossil fuel.
His work is dedicated to discovering how Statistics, National forest inventory are connected with Decision support system and other disciplines.
His Sampling research integrates issues from Dead wood, Forest inventory, Plot and Sample.
His Biodiversity research extends to National forest, which is thematically connected.
Between 2010 and 2021, his most popular works were:
- Specialist species of wood‐inhabiting fungi struggle while generalists thrive in fragmented boreal forests (135 citations)
- A meta-analysis and review of the literature on the k-Nearest Neighbors technique for forestry applications that use remotely sensed data (79 citations)
- Designing and Conducting a Forest Inventory - case: 9th National Forest Inventory of Finland (58 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Ecology
- Biodiversity
His main research concerns National forest inventory, Forest inventory, Forestry, Renewable energy and Biofuel.
Erkki Tomppo has researched National forest inventory in several fields, including Decision tree and Decision support system.
Erkki Tomppo performs integrative study on Forest inventory and Variance.
His Forestry study incorporates themes from Ancillary data, Field and k-nearest neighbors algorithm.
Remote sensing covers Erkki Tomppo research in Ancillary data.
His Remote sensing study frequently draws connections between adjacent fields such as Data mining.
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