H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Environmental Sciences D-index 36 Citations 7,100 138 World Ranking 4077 National Ranking 65

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Ecology
  • Artificial intelligence

Mikko Vastaranta mainly investigates Remote sensing, Forest inventory, Point cloud, Laser scanning and Tree. His Remote sensing study combines topics in areas such as Mean squared error, Diameter at breast height and Random forest. He has researched Forest inventory in several fields, including Descriptive statistics, Photogrammetry, Aboveground biomass, Vegetation and Lidar.

His study in Point cloud is interdisciplinary in nature, drawing from both Ecology and Algorithm. His research in Laser scanning intersects with topics in Sample, Field and Scale. His Tree research includes themes of Terrestrial laser scanning and Statistics, Spatial analysis, Plot.

His most cited work include:

  • Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data (327 citations)
  • An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning (302 citations)
  • Terrestrial laser scanning in forest inventories (276 citations)

What are the main themes of his work throughout his whole career to date?

Mikko Vastaranta mainly focuses on Remote sensing, Forest inventory, Lidar, Laser scanning and Tree. His Remote sensing study combines topics from a wide range of disciplines, such as Point cloud and Canopy, Tree canopy. His Point cloud research is multidisciplinary, incorporating elements of Scots pine, Terrestrial laser scanning, Mean squared error, Aboveground biomass and Biomass.

His Forest inventory research focuses on subjects like Basal area, which are linked to Standard deviation. His research in Lidar focuses on subjects like Vegetation, which are connected to Hyperspectral imaging. His study in the field of Tree inventory also crosses realms of Benchmarking.

He most often published in these fields:

  • Remote sensing (77.84%)
  • Forest inventory (40.00%)
  • Lidar (41.08%)

What were the highlights of his more recent work (between 2018-2021)?

  • Remote sensing (77.84%)
  • Scots pine (19.46%)
  • Taiga (17.30%)

In recent papers he was focusing on the following fields of study:

Remote sensing, Scots pine, Taiga, Forest inventory and Point cloud are his primary areas of study. His Remote sensing study incorporates themes from Tree health, Canopy and Laser scanning. His Scots pine research includes elements of Forest management, Parametrization, Volume and Mean squared error.

His Forest inventory research includes themes of Tree and Basal area. The Tree study combines topics in areas such as Sample and Statistics. Point cloud and Pinus are frequently intertwined in his study.

Between 2018 and 2021, his most popular works were:

  • Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle (14 citations)
  • Characterizing Seedling Stands Using Leaf-Off and Leaf-On Photogrammetric Point Clouds and Hyperspectral Imagery Acquired from Unmanned Aerial Vehicle (14 citations)
  • Examining Changes in Stem Taper and Volume Growth with Two-Date 3D Point Clouds (13 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Ecology
  • Artificial intelligence

His scientific interests lie mostly in Remote sensing, Forest inventory, Canopy, Lidar and Taiga. His studies deal with areas such as Picea abies, Climate change, Scots pine, Forestry and Laser scanning as well as Remote sensing. His work investigates the relationship between Forest inventory and topics such as Tree that intersect with problems in Soil science.

His Lidar research is multidisciplinary, incorporating perspectives in Tree health, Vegetation and Infestation. His Taiga research integrates issues from Point cloud, Statistics, Pairwise comparison, Sample and Sustainable forest management. His work carried out in the field of Point cloud brings together such families of science as Coarse woody debris, Basal area, Sample, Terrestrial laser scanning and Sample plot.

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.

Best Publications

An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning

Harri Kaartinen;Juha Hyyppä;Xiaowei Yu;Mikko Vastaranta.
Remote Sensing (2012)

430 Citations

Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data

Pasi Raumonen;Mikko Kaasalainen;Markku Åkerblom;Sanna Kaasalainen.
Remote Sensing (2013)

421 Citations

Terrestrial laser scanning in forest inventories

Xinlian Liang;Xinlian Liang;Ville Kankare;Ville Kankare;Juha Hyyppä;Juha Hyyppä;Yunsheng Wang;Yunsheng Wang.
Isprs Journal of Photogrammetry and Remote Sensing (2016)

380 Citations

Remote Sensing Technologies for Enhancing Forest Inventories: A Review

Joanne C. White;Nicholas C. Coops;Michael A. Wulder;Mikko Vastaranta.
Canadian Journal of Remote Sensing (2016)

342 Citations

Predicting individual tree attributes from airborne laser point clouds based on the random forests technique

Xiaowei Yu;Juha Hyyppä;Mikko Vastaranta;Markus Holopainen.
Isprs Journal of Photogrammetry and Remote Sensing (2011)

325 Citations

The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

Joanne C. White;Michael A. Wulder;Mikko Vastaranta;Nicholas C. Coops.
Forests (2013)

275 Citations

A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach

Joanne C. White;Michael A. Wulder;Andrés Varhola;Mikko Vastaranta.
Forestry Chronicle (2013)

234 Citations

Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning

Xinlian Liang;P. Litkey;J. Hyyppa;H. Kaartinen.
IEEE Transactions on Geoscience and Remote Sensing (2012)

232 Citations

Individual tree biomass estimation using terrestrial laser scanning

Ville Kankare;Markus Holopainen;Mikko Vastaranta;Eetu Puttonen.
Isprs Journal of Photogrammetry and Remote Sensing (2013)

219 Citations

Airborne laser scanning and digital stereo imagery measures of forest structure: comparative results and implications to forest mapping and inventory update

Mikko Vastaranta;Michael A. Wulder;Joanne C. White;Anssi Pekkarinen.
Canadian Journal of Remote Sensing (2013)

178 Citations

If you think any of the details on this page are incorrect, let us know.

Contact us

Best Scientists Citing Mikko Vastaranta

Juha Hyyppä

Juha Hyyppä

Finnish Geospatial Research Institute

Publications: 87

Nicholas C. Coops

Nicholas C. Coops

University of British Columbia

Publications: 74

Erik Næsset

Erik Næsset

Norwegian University of Life Sciences

Publications: 47

Xinlian Liang

Xinlian Liang

Finnish Geospatial Research Institute

Publications: 46

Terje Gobakken

Terje Gobakken

Norwegian University of Life Sciences

Publications: 46

Antero Kukko

Antero Kukko

Aalto University

Publications: 45

Mathias Disney

Mathias Disney

University College London

Publications: 41

Joanne C. White

Joanne C. White

Natural Resources Canada

Publications: 41

Harri Kaartinen

Harri Kaartinen

University of Turku

Publications: 41

Matti Maltamo

Matti Maltamo

University of Eastern Finland

Publications: 40

Michael A. Wulder

Michael A. Wulder

Natural Resources Canada

Publications: 40

Kim Calders

Kim Calders

Ghent University

Publications: 38

Marco Heurich

Marco Heurich

University of Freiburg

Publications: 36

Norbert Pfeifer

Norbert Pfeifer

TU Wien

Publications: 32

Anttoni Jaakkola

Anttoni Jaakkola

Finnish Geospatial Research Institute

Publications: 30

Qinghua Guo

Qinghua Guo

Chinese Academy of Sciences

Publications: 26

Something went wrong. Please try again later.