What is he best known for?
The fields of study he is best known for:
- Ecology
- Statistics
- Ecosystem
Kim Calders mainly focuses on Remote sensing, Lidar, Point cloud, Tree and Mean squared error.
The study incorporates disciplines such as Canopy, Phenology, Vegetation, Scale and Laser scanning in addition to Remote sensing.
His Vegetation research includes elements of Forest management and Sustainable development.
His Lidar study combines topics from a wide range of disciplines, such as Forest inventory, Atmospheric sciences, Allometry and Understory.
His Point cloud study integrates concerns from other disciplines, such as Tree structure, Ground truth and Plot.
His studies in Tree integrate themes in fields like Range and Concordance correlation coefficient.
His most cited work include:
- Nondestructive estimates of above‐ground biomass using terrestrial laser scanning (285 citations)
- SimpleTree —An Efficient Open Source Tool to Build Tree Models from TLS Clouds (118 citations)
- Terrestrial Laser Scanning for Plot-Scale Forest Measurement (115 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of investigation include Lidar, Remote sensing, Tree, Ecology and Tree structure.
His Lidar research includes themes of Point cloud, Canopy, Atmospheric sciences, Mean squared error and Vegetation.
Temperate forest is closely connected to Laser scanning in his research, which is encompassed under the umbrella topic of Point cloud.
His work carried out in the field of Remote sensing brings together such families of science as Terrestrial laser scanning, Scale, Leaf area index and Plot.
His studies deal with areas such as Biomass, Radiative transfer and Propagation of uncertainty as well as Tree.
His Tree structure research incorporates themes from Agroforestry and Thinning.
He most often published in these fields:
- Lidar (49.11%)
- Remote sensing (45.54%)
- Tree (22.32%)
What were the highlights of his more recent work (between 2019-2021)?
- Biomass (16.96%)
- Ecology (29.46%)
- Tree (22.32%)
In recent papers he was focusing on the following fields of study:
Kim Calders focuses on Biomass, Ecology, Tree, Forest management and Tree allometry.
Kim Calders interconnects Vegetation, Forestry, Allometry and Alder in the investigation of issues within Biomass.
His work investigates the relationship between Vegetation and topics such as Temperate forest that intersect with problems in Canopy.
His work in the fields of Tree, such as Tree structure, intersects with other areas such as Observational error.
His work in Forest ecology addresses issues such as Sensor fusion, which are connected to fields such as Remote sensing.
Kim Calders focuses mostly in the field of Remote sensing, narrowing it down to topics relating to Hemispherical photography and, in certain cases, Lidar.
Between 2019 and 2021, his most popular works were:
- Improved Supervised Learning-Based Approach for Leaf and Wood Classification From LiDAR Point Clouds of Forests (14 citations)
- Terrestrial laser scanning in forest ecology: Expanding the horizon (13 citations)
- 3D imaging insights into forests and coral reefs (10 citations)
In his most recent research, the most cited papers focused on:
- Ecology
- Statistics
- Ecosystem
His primary areas of study are Tree, Ecology, Coral reef, Ecology and Climate change.
In the subject of general Tree, his work in Tree structure is often linked to Function, thereby combining diverse domains of study.
His research integrates issues of Allometry, Biomass, Tropical savanna climate, Vegetation and Crown in his study of Tree structure.
Ecosystem and Threatened species are the core of his Ecology study.
His Tree allometry research is multidisciplinary, incorporating elements of Calibration, Statistics, Multivariate statistics and Linear regression.
The various areas that Kim Calders examines in his Physical geography study include Land cover, Temperate forest, Biodiversity and Canopy.
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