KATALIN WAGA
Postdoctoral Researcher
Katalin Waga is a Postdoctoral Researcher at the University of Eastern Finland. She has a background in geography (M.Sc, Eötvös Loránd University, Hungary) and forestry (M.Sc., University of Eastern Finland). She received her Ph.D. (2021) from the University of Eastern Finland.
Her current research interest focuses on the quality assessment of unpaved forest road assessments. She works primarily with airborne LiDAR data and other remote sensing datasets.
Contact info
Organization
Faculty of Science and Forestry, School of Forest Sciences
katalin.waga@uef.fi
Phone
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Keywords
Research groups - UEF
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Forest-Human-Machine Interplay - Building Resilience, Redefining Value Networks and Enabling Meaningful Experiences (UNITE) -
Vastaranta Research Syndicate
Links
Publications
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Waga, Katalin (ed.) . 2021. Unpaved forest road quality assessment using airborne LiDAR data. Finnish Society of Forest Science; Faculty of Agriculture and Forestry of the University of Helsinki; School of Forest Sciences of the University of Eastern Finland. Dissertationes forestales 316. 2021
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Waga, Katalin; Malinen, Jukka; Tokola, Timo. 2021. Locally invariant analysis of forest road quality using two different pulse density airborne laser scanning datasets Silva fennica 55 1: 10371. 2021
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Waga, Katalin; Malinen, Jukka; Tokola, Timo. 2020. A Topographic Wetness Index for Forest Road Quality Assessment: An Application in the Lakeland Region of Finland Forests 11 11: 1165. 2020
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Waga, Katalin; Tompalski, Piotr; Coops, Nicholas C; White, Joanne C; Wulder, Michael A; Malinen, Jukka; Tokola, Timo. 2019. Forest Road Status Assessment Using Airborne Laser Scanning Forest science [Epub ahead of print 6 Oct 2019]: 1-8. 2019
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Kiss Katalin, Malinen Jukka, Tokola Timo. 2016. Comparison of high and low density airborne lidar data for forest road quality assessment. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences 3 8: 167-172. 2016
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Kiss Katalin, Malinen Jukka, Tokola Timo. 2015. Forest road quality control using ALS data. CANADIAN JOURNAL OF FOREST RESEARCH 45 11: 1636-1642. 2015