{"id":194,"date":"2026-05-07T10:06:47","date_gmt":"2026-05-07T07:06:47","guid":{"rendered":"https:\/\/sites.uef.fi\/dp-fobi\/?page_id=194"},"modified":"2026-06-10T15:17:24","modified_gmt":"2026-06-10T12:17:24","slug":"multi-temporal-laser-scanning","status":"publish","type":"page","link":"https:\/\/sites.uef.fi\/dp-fobi\/multi-temporal-laser-scanning\/","title":{"rendered":"Multi-temporal laser scanning for characterizing tree structure, growth, and wood quality"},"content":{"rendered":"<p><a href=\"https:\/\/uef.varbi.com\/en\/what:job\/jobID:945076\/\"><button>APPLY FOR THIS PhD POSITION <\/button><\/a> <strong>Application period: 11 June \u2013 10 August, 2026<\/strong><\/p>\n\n\n<h2 class=\"wp-block-heading\">Research project description<\/h2>\n\n\n\n<p>Sustainable forest management depends on measurements taken from individual trees and forest stands. However, the vast scale of forests, their long growth cycles, and the structural complexity of trees make data collection and analysis challenging. Laser scanning technology offers transformative methods for measuring and monitoring forests. It operates by emitting laser pulses to measure distances to surrounding objects, creating high-resolution 3D point clouds of the environment. By leveraging multi-temporal (time-series) close-range laser scanning data\u2014collected from static or kinematic, terrestrial or low-altitude platforms\u2014this research aims to develop advanced methodologies to address the following questions:<\/p>\n\n\n\n<ol start=\"1\" class=\"wp-block-list\">\n<li>How can tree structures be characterized using various laser scanning techniques?<\/li>\n\n\n\n<li>How can laser scanning time-series be utilized to quantify tree growth?<\/li>\n\n\n\n<li>How can precise measurements of tree structure and dynamics be integrated to assess wood quality in standing trees?<\/li>\n<\/ol>\n\n\n\n<p><strong>This research seeks to enhance forest mensuration, providing novel methods and insights for both the scientific community and practical forestry organizations responsible for large-scale data collection and forest resource management<\/strong>.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Academic background and skills of the applicant<\/h2>\n\n\n\n<p>An ideal candidate holds <strong>a master\u2019s degree in a relevant field such as forestry, geography, geoinformatics, applied statistics, or a closely related discipline.<\/strong> The candidate is expected to demonstrate proficiency in remote sensing data analysis and the ability to manage and process large datasets. Excellent written and oral communication skills in English are essential for the position. The selected candidate must fulfil the language skills requirements of the Doctoral Programme in Science, Forestry and Technology at UEF (see <a href=\"https:\/\/www.uef.fi\/en\/degree-programme\/doctoral-programme-in-science-forestry-and-technology\">https:\/\/www.uef.fi\/en\/degree-programme\/doctoral-programme-in-science-forestry-and-technology<\/a> (Eligibility and admission criteria)). The role requires the capability to conduct independent fieldwork, including possession of a valid driver\u2019s license and a willingness to travel or work abroad. Familiarity with relevant programming environments, such as Python, R, or MATLAB, is considered an advantage. A proactive and independent approach to research and problem-solving is required.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Doctoral programme and research group<\/h2>\n\n\n\n<p>Doctoral education in the University of Eastern Finland is arranged in seven discipline specific or thematic doctoral programmes. This research project will be located in the <a href=\"https:\/\/www.uef.fi\/en\/degree-programme\/doctoral-programme-in-science-forestry-and-technology\">Doctoral Programme in Science, Forestry and Technology<\/a>, and the submitting department is the <a href=\"https:\/\/www.uef.fi\/en\/unit\/school-of-forest-sciences\">School of Forest Sciences<\/a>.<\/p>\n\n\n\n<p>The candidate will join the international research group led by Professor Vastaranta at the University of Eastern Finland (UEF). Currently consisting of approximately 15 researchers from China, India, Nepal, Belgium, Latvia, and Finland, the group provides a vibrant and multicultural academic environment.<\/p>\n\n\n\n<p>The group specializes in developing cutting-edge remote sensing and geospatial technologies to measure, monitor, and better understand forest ecosystems. Laser scanning is at the core of their expertise. For example, they develop highly accurate and efficient technologies for forest characterization, with a specific focus on terrestrial and mobile laser scanning (TLS\/MLS). Furthermore, they utilize laser scanning time-series data to analyze the development of individual trees and forest ecosystems, and to pioneer novel monitoring methodologies. The research group is an integral part of the UNITE Flagship (Forest-Human-Machine Interplay), which brings together world-class expertise in forest sciences, geospatial technologies, and gamification.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Partners \/ Secondments<\/h2>\n\n\n\n<p>National Land Survey of Finland, hosted by Juha Hyypp\u00e4<\/p>\n\n\n\n<p>University of Helsinki, Finland, hosted by Markus Holopainen<\/p>\n\n\n\n<p>Ghent University, Belgium, hosted by Kim Calders<\/p>\n\n\n\n<h2 class=\"wp-block-heading\"><strong>Other interdisciplinary, international and\/or intersectoral collaboration<\/strong><\/h2>\n\n\n\n<p>Intersectoral and interdisciplinary collaboration is strengthened through DP-FOBI&#8217;s three summer schools involving academic supervisors, non-academic partners, and other stakeholders, enabling hands-on interaction and knowledge exchange.<\/p>\n\n\n\n<h2 class=\"wp-block-heading\">Supervisors and related research<\/h2>\n\n\n\t<div id=\"accordion-block_eb2de6dce38b94952f441402be9c67bd\" class=\"accordions\">\n\t\t\t\t\t<div class=\"accordion accordion-js\">\n\t\t\t\t<button class=\"accordion__button\" aria-controls=\"content-3374\" aria-expanded=\"false\" id=\"accordion-control-3374\">\n\t\t\t\t\t<h3 class=\"accordion__heading\" >\n\t\t\t\t\t\tMikko Vastaranta\t\t\t\t\t<\/h3>\n\t\t\t\t<\/button>\n\t\t\t\t<div class=\"accordion__content\" role=\"region\" aria-labelledby=\"accordion-control-3374\" aria-hidden=\"true\" id=\"content-3374\">\n\t\t\t\t\t<p>Dr. <a href=\"https:\/\/uefconnect.uef.fi\/en\/mikko.vastaranta\/\">Mikko Vastaranta<\/a> is a Professor at the University of Eastern Finland\u2019s School of Forest Sciences. He earned his M.Sc. (2007) and PhD (2012) in Forest Resource Science and Technology from the University of Helsinki, where he also holds an Adjunct Professorship in Forest Remote Sensing. His previous professional experience includes positions as a Research Scientist at the Centre of Excellence in Laser Scanning Research, University Lecturer in Forest Planning at the University of Helsinki, and international roles as a Visiting Research Scientist at the Pacific Forestry Centre (Natural Resources Canada) and a Visiting Professor at Shinshu University (Japan).<\/p>\n<p>Professor Vastaranta\u2019s research focuses on developing remote sensing and geospatial technologies to measure, monitor, and better understand forest ecosystems. He has authored over 150 peer-reviewed scientific articles, including seven &#8220;Highly Cited\/Hot Papers&#8221; according to Web of Science. His work has been published in leading journals such as ISPRS Journal of Photogrammetry and Remote Sensing, Forest Ecology and Management, and Remote Sensing of Environment.<\/p>\n<p>In recognition of his contributions to the field, he has been named &#8220;Forester of the Year&#8221; in Finland and received the Canadian Forest Service\u2019s Recognition Award for Collaboration.<\/p>\n<p>Professor Vastaranta has a strong track record in doctoral supervision, having guided 16 PhD students to completion. His former students have achieved significant academic success: three currently hold professorships, one is ranked among the world&#8217;s most highly cited researchers, and his mentees have also successfully secured prestigious independent research funds.<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<div class=\"accordion accordion-js\">\n\t\t\t\t<button class=\"accordion__button\" aria-controls=\"content-2617\" aria-expanded=\"false\" id=\"accordion-control-2617\">\n\t\t\t\t\t<h3 class=\"accordion__heading\" >\n\t\t\t\t\t\tTuomas Yrttimaa\t\t\t\t\t<\/h3>\n\t\t\t\t<\/button>\n\t\t\t\t<div class=\"accordion__content\" role=\"region\" aria-labelledby=\"accordion-control-2617\" aria-hidden=\"true\" id=\"content-2617\">\n\t\t\t\t\t<p>Dr. <a href=\"https:\/\/uefconnect.uef.fi\/en\/tuomas.yrttimaa\/\">Tuomas Yrttimaa<\/a> is an Assistant Professor of Forest Information Technologies at the School of Forest Sciences, University of Eastern Finland. He obtained his M.Sc. degree from the University of Helsinki in 2018 and completed his Ph.D. at the University of Eastern Finland in 2021, where his doctoral research focused on advancing laser scanning methodologies for detailed forest structural analysis.<\/p>\n<p>Dr. Yrttimaa\u2019s expertise centers on close-range laser scanning technologies, including terrestrial and mobile laser scanning, with a strong emphasis on extracting high-resolution, three-dimensional information from forest environments. His work integrates advanced computational approaches in point cloud processing, enabling precise characterization of tree architecture, stem geometry, and canopy structure. A key aspect of his research is the development of frameworks for efficient data acquisition and analysis.<\/p>\n<p>Dr. Yrttimaa is particularly interested in linking detailed structural information derived from point clouds to ecological and wood property assessments, supporting applications in forest management, resource assessment, and wood traceability. His work bridges methodological development and applied forest science, promoting the operational adoption of laser scanning technologies. Through his research, he has demonstrated strong competence in combining remote sensing, computational geometry, and data-driven modeling, positioning him as an emerging expert in forest measurement technologies and digital forestry.<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t\t\t<div class=\"accordion accordion-js\">\n\t\t\t\t<button class=\"accordion__button\" aria-controls=\"content-2905\" aria-expanded=\"false\" id=\"accordion-control-2905\">\n\t\t\t\t\t<h3 class=\"accordion__heading\" >\n\t\t\t\t\t\tRelated articles\t\t\t\t\t<\/h3>\n\t\t\t\t<\/button>\n\t\t\t\t<div class=\"accordion__content\" role=\"region\" aria-labelledby=\"accordion-control-2905\" aria-hidden=\"true\" id=\"content-2905\">\n\t\t\t\t\t<p>Kamula T, Yrttimaa T, Cimdins R, Polvivaara A, Kukko A, Holopainen M, Vastaranta M (2026) Bi-temporal terrestrial laser scanning to measure secondary growth of tree: toward non-destructive assessment of wood properties. Scandinavian Journal of Forest Research, 1\u201316.<\/p>\n<p>Kamula, T., Yrttimaa, T., Erkkil\u00e4, A., Liikonen, L. and Vastaranta, M., 2025. Benefits of using multi-return terrestrial laser scanning for tree characterization in southern boreal forests.\u00a0<em>Remote Sensing of Environment<\/em>,\u00a0<em>329<\/em>, p.114921.<\/p>\n<p>Poorazimy, M., Ronoud, G., Yrttimaa, T., Hyypp\u00e4, J., Saarinen, N., Kankare, V. and Vastaranta, M., 2025. An integrated approach combining bi-temporal airborne laser scanning and X-ray microdensitometry in assessing wood properties.\u00a0<em>Forest Ecology and Management<\/em>,\u00a0<em>585<\/em>, p.122497.<\/p>\n<p>Yrttimaa, T., Junttila, S., Hyypp\u00e4, J., Holopainen, M., Wulder, M.A. and Vastaranta, M., 2025. Quantifying architectural uniqueness of Scots pine trees using terrestrial laser scanning: toward individual tree fingerprinting.\u00a0<em>Forestry: An International Journal of Forest Research<\/em>,\u00a0<em>98<\/em>(4), pp.465-477.<\/p>\n<p>Yrttimaa T, Junttila S, Luoma V, Calders K, Kankare V, Saarinen N, Kukko A, Holopainen M, Hyypp\u00e4 J, Vastaranta M (2023) Capturing seasonal radial growth of boreal trees with terrestrial laser scanning. Forest Ecology and Management, 529, 120733.<\/p>\n<p>Yrttimaa T, Kankare V, Luoma V, Junttila S, Saarinen N, Calders K, Holopainen M, Hyypp\u00e4 J, Vastaranta M (2024) A method for identifying and segmenting branches of Scots pine (Pinus sylvestris L.) trees using terrestrial laser scanning. Forestry: An International Journal of Forest Research, 97(4), 531-545.<\/p>\n<p>&nbsp;<\/p>\n\t\t\t\t<\/div>\n\t\t\t<\/div>\n\t\t\t<\/div>\n\t","protected":false},"excerpt":{"rendered":"<p>APPLY FOR THIS PhD POSITION Application period: 11 June \u2013 10 August, 2026 Research project description Sustainable forest management depends on measurements taken from individual trees and forest stands. However, the vast scale of forests, their long growth cycles, and the structural complexity of trees make data collection and analysis challenging. Laser scanning technology offers [&hellip;]<\/p>\n","protected":false},"author":1364,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"_acf_changed":false,"footnotes":""},"class_list":["post-194","page","type-page","status-publish","hentry"],"acf":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v27.5 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>Multi-temporal laser scanning for characterizing tree structure, growth, and wood quality - Doctoral Programme for Advancing Forest-Based Bioeconomy (DP-FOBI)<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/sites.uef.fi\/dp-fobi\/multi-temporal-laser-scanning\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Multi-temporal laser scanning for characterizing tree structure, growth, and wood quality - Doctoral Programme for Advancing Forest-Based Bioeconomy (DP-FOBI)\" \/>\n<meta property=\"og:description\" content=\"APPLY FOR THIS PhD POSITION Application period: 11 June \u2013 10 August, 2026 Research project description Sustainable forest management depends on measurements taken from individual trees and forest stands. 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