H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Engineering and Technology D-index 70 Citations 15,503 297 World Ranking 279 National Ranking 1
Environmental Sciences D-index 72 Citations 17,943 332 World Ranking 514 National Ranking 8

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Remote sensing
  • Statistics

Remote sensing, Laser scanning, Point cloud, Forest inventory and Lidar are his primary areas of study. His Remote sensing research is multidisciplinary, incorporating perspectives in Tree, Canopy and Crown. His Laser scanning research is multidisciplinary, relying on both Change detection, Computer vision, Artificial intelligence and Mobile mapping.

His Point cloud research includes elements of Quality, Plot, Real-time computing, Forest ecology and Digital surface. His Forest inventory study integrates concerns from other disciplines, such as Satellite imagery, Basal area, Sampling, Mean squared error and Feature extraction. His study explores the link between Lidar and topics such as Radiometry that cross with problems in RGB color model and Multilayer perceptron.

His most cited work include:

  • A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners (572 citations)
  • Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests (459 citations)
  • Laser scanning of forest resources: the nordic experience (404 citations)

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

His scientific interests lie mostly in Remote sensing, Laser scanning, Lidar, Point cloud and Forest inventory. His studies deal with areas such as Tree, Canopy and Radar as well as Remote sensing. His study looks at the intersection of Laser scanning and topics like Artificial intelligence with Pattern recognition.

Juha Hyyppä has researched Lidar in several fields, including Ranging, Hyperspectral imaging and Multispectral image. His research in Point cloud intersects with topics in Terrestrial laser scanning, Photogrammetry, GNSS applications and Scots pine. Juha Hyyppä has included themes like Basal area, Remote sensing, Tree canopy, Statistics and Taiga in his Forest inventory study.

He most often published in these fields:

  • Remote sensing (63.18%)
  • Laser scanning (41.87%)
  • Lidar (25.42%)

What were the highlights of his more recent work (between 2016-2021)?

  • Remote sensing (63.18%)
  • Lidar (25.42%)
  • Point cloud (25.42%)

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

Juha Hyyppä mostly deals with Remote sensing, Lidar, Point cloud, Laser scanning and Forest inventory. The Remote sensing study combines topics in areas such as Canopy, Random forest and Taiga. As part of the same scientific family, he usually focuses on Lidar, concentrating on Radar and intersecting with Ku band.

His Point cloud study combines topics in areas such as Tree, Photogrammetry and Scots pine. His Laser scanning research incorporates themes from Data processing, GNSS applications and Inertial measurement unit. Juha Hyyppä has researched Forest inventory in several fields, including Basal area, Deciduous, Tree canopy, Statistics and Crown.

Between 2016 and 2021, his most popular works were:

  • Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging (171 citations)
  • International benchmarking of terrestrial laser scanning approaches for forest inventories (96 citations)
  • Comparison of the Selected State-Of-The-Art 3D Indoor Scanning and Point Cloud Generation Methods (81 citations)

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

  • Artificial intelligence
  • Statistics
  • Ecology

Juha Hyyppä mainly focuses on Remote sensing, Point cloud, Tree, Lidar and Forest inventory. His Remote sensing study combines topics from a wide range of disciplines, such as Mean squared error, Random forest and Laser scanning. His Point cloud research includes elements of Terrestrial laser scanning, Real-time computing and Data collection.

His work deals with themes such as Statistics, Plot, RGB color model, Reference data and Taiga, which intersect with Tree. His Lidar research integrates issues from Change detection, Data processing, Feature, Canopy and Water content. His Forest inventory study incorporates themes from Diameter at breast height, Terrain, Basal area and Tree canopy.

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

A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners

J. Hyyppa;O. Kelle;M. Lehikoinen;M. Inkinen.
IEEE Transactions on Geoscience and Remote Sensing (2001)

788 Citations

Review of methods of small-footprint airborne laser scanning for extracting forest inventory data in boreal forests

J. Hyyppä;H. Hyyppä;D. Leckie;F. Gougeon.
International Journal of Remote Sensing (2008)

633 Citations

Laser scanning of forest resources: the nordic experience

Erik Næsset;Terje Gobakken;Johan Holmgren;Hannu Hyyppä.
Scandinavian Journal of Forest Research (2004)

548 Citations

Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes

Juha Hyyppä;Hannu Hyyppä;Mikko Inkinen;Marcus Engdahl.
decision support systems (2000)

506 Citations

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

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

Estimation of timber volume and stem density based on scanning laser altimetry and expected tree size distribution functions

Matti Maltamo;K. Eerikäinen;Juho Pitkänen;Juha Hyyppä.
Remote Sensing of Environment (2004)

379 Citations

Automatic detection of harvested trees and determination of forest growth using airborne laser scanning

Xiaowei Yu;Juha Hyyppä;Harri Kaartinen;Matti Maltamo.
Remote Sensing of Environment (2004)

360 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

Mini-UAV-Borne LIDAR for Fine-Scale Mapping

Yi Lin;J Hyyppä;A Jaakkola.
IEEE Geoscience and Remote Sensing Letters (2011)

316 Citations

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