Publications

Polvivaara A, Korpela I, Vastaranta M, Junttila S: Detecting tree mortality using waveform features of airborne LiDAR. In: Remote Sensing of Environment, vol. 303, 2024, ISSN: 0034-4257. (Type: Journal Article | Abstract | Links)

@article{bad50daa2d444d99a0e35e6d3003fb60,

title = {Detecting tree mortality using waveform features of airborne LiDAR},

author = {Antti Polvivaara and Ilkka Korpela and Mikko Vastaranta and Samuli Junttila},

doi = {10.1016/j.rse.2024.114019},

issn = {0034-4257},

year  = {2024},

date = {2024-03-15},

journal = {Remote Sensing of Environment},

volume = {303},

publisher = {EXCERPTA MEDICA INC-ELSEVIER SCIENCE INC},

abstract = {Tree mortality impacts biodiversity, carbon dynamics and the management of forests. Climate change is expected to increase tree mortality, but understanding of tree mortality rates and the underlying processes is limited; thus, more accurate and efficient tree mortality mapping methods are required. In this study, we investigated the feasibility of using airborne light detection and ranging (LiDAR) waveform (WF) features in detecting dead trees to monitor tree mortality and studied how the WF features of dead trees change over time. We used three consecutive LiDAR campaigns using fixed sensor and flight parameters in a boreal forest in Southern Finland (61.5(degrees)N, 24.2(degrees)E). The campaigns spanned four years and were carried out in 2011, 2013 and 2015. A Riegl LMSQ680i LiDAR sensor, which operates at 1550 nm wavelength, provided return WF data to study the geometricoptical properties of living and dead trees and monitor mortality of Norway spruce (Picea abies H. Karst.). Our findings highlight the differences in radiometric and geometric WF features between living and dead trees. The return WFs from dead trees were consistently elongated and contained more backscattering energy. We also found that as a tree died, the canopy and branch structures became less dense and more irregular, leading to more complex return WFs. The WF features were used for binary classification of living and dead trees, resulting in classification accuracies between 94.7 and 98.5%, depending on the campaign. Distinguishing between living and dead trees is challenging for trees that have died recently when there are only minor defects in the crown and discoloration of foliage. Tree decay after death improved the discernability between living and dead trees as the geometric-optical properties of the crown change. The radiometric and geometric WF features and canopy mortality effects on the WF features are consistent across datasets implying intrinsic quality of information in the WF features. The within-class variance of WF features in dead trees is greater than that in living trees, indicating significant variations in the geometric and radiometric properties of trees between stages of decaying and dying. Our results imply that LiDAR WFs can be used for the accurate detection of dead trees to map tree mortality.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Close

Tree mortality impacts biodiversity, carbon dynamics and the management of forests. Climate change is expected to increase tree mortality, but understanding of tree mortality rates and the underlying processes is limited; thus, more accurate and efficient tree mortality mapping methods are required. In this study, we investigated the feasibility of using airborne light detection and ranging (LiDAR) waveform (WF) features in detecting dead trees to monitor tree mortality and studied how the WF features of dead trees change over time. We used three consecutive LiDAR campaigns using fixed sensor and flight parameters in a boreal forest in Southern Finland (61.5(degrees)N, 24.2(degrees)E). The campaigns spanned four years and were carried out in 2011, 2013 and 2015. A Riegl LMSQ680i LiDAR sensor, which operates at 1550 nm wavelength, provided return WF data to study the geometricoptical properties of living and dead trees and monitor mortality of Norway spruce (Picea abies H. Karst.). Our findings highlight the differences in radiometric and geometric WF features between living and dead trees. The return WFs from dead trees were consistently elongated and contained more backscattering energy. We also found that as a tree died, the canopy and branch structures became less dense and more irregular, leading to more complex return WFs. The WF features were used for binary classification of living and dead trees, resulting in classification accuracies between 94.7 and 98.5%, depending on the campaign. Distinguishing between living and dead trees is challenging for trees that have died recently when there are only minor defects in the crown and discoloration of foliage. Tree decay after death improved the discernability between living and dead trees as the geometric-optical properties of the crown change. The radiometric and geometric WF features and canopy mortality effects on the WF features are consistent across datasets implying intrinsic quality of information in the WF features. The within-class variance of WF features in dead trees is greater than that in living trees, indicating significant variations in the geometric and radiometric properties of trees between stages of decaying and dying. Our results imply that LiDAR WFs can be used for the accurate detection of dead trees to map tree mortality.

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Polvivaara A, Korpela I, Junttila S, Vastaranta M: Detecting tree mortality using waveform features of airborne LiDAR. In: 2024. (Type: Journal Article | Links)

Junttila S, Blomqvist M, Laukkanen V, O’Sullivan H, Polvivaara A, Holopainen M, Peltola H: Significant increase observed in tree mortality in boreal forests in Southern Finland. In: 2024. (Type: Journal Article | Links)

O’Sullivan H, Junttila S: Quantifying the Hydraulic Health of Fennoscandian Boreal Forests in a Changing Climate. In: 2024. (Type: Journal Article | Links)

Yrttimaa T, Junttila S, Luoma V, Pyörälä J, Puttonen E, Campos M, Holttä T, Vastaranta M: Tree height and stem growth dynamics in a Scots pine dominated boreal forest. In: Trees, forests and people, vol. 15, 2024, ISSN: 2666-7193. (Type: Journal Article | Abstract | Links)

@article{813aa87fc66642f288bbde5f1896e880,

title = {Tree height and stem growth dynamics in a Scots pine dominated boreal forest},

author = {Tuomas Yrttimaa and Samuli Junttila and Ville Luoma and Jiri Pyörälä and Eetu Puttonen and Mariana Campos and Teemu Holttä and Mikko Vastaranta},

doi = {10.1016/j.tfp.2023.100468},

issn = {2666-7193},

year  = {2024},

date = {2024-03-01},

journal = {Trees, forests and people},

volume = {15},

publisher = {Elsevier},

abstract = {Tree growth is a key forest ecosystem service and essential for carbon sequestration and biomass production. However, the intra-seasonal dynamics of tree height and stem diameter growth have been difficult to measure hampering the understanding of the interplay between these processes. Here, we investigated the feasibility of a laser scanning system in monitoring tree height development, aiming to study how tree height and stem diameter growth dynamics vary and interact, and how environmental variables explain the tree growth dynamics within a growing season. The experimental design consisted of 40 boreal trees equipped with dendrometers measuring changes in the stem diameter at 15-minutes intervals while a laser scanner fixed to a 35-meter tower was used to measure tree height near-daily during the monitoring period from May to mid-August 2021. We found that vertical changes in the tree-segmented point clouds enabled monitoring of tree height increment and investigation of the temporal dynamics of changes in tree height and stem diameter, when coupled with dendrometer measurements. The experiments revealed that, on average, height increment occurred ahead of diameter increment and deviated more towards the late season. Norway spruce showed more delayed diameter increment than Scots pine during the late season. Silver birch experienced diameter increment ahead of height increment. Based on the dendrometer measurements, we computed a radial change response function that aimed at characterizing the current state of stem diameter development, whether it was increasing or decreasing from its past state. When these radial change responses were compared against environmental variables, we found that the radial change response was mostly controlled by balance between precipitation and evapotranspiration, soil water content, minimum daily temperature, and vapor pressure deficit. Our findings support the utilization of laser scanning time series for measuring intra-seasonal changes in tree height and increase our understanding of the interactions between tree height and stem diameter growth processes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Close

Tree growth is a key forest ecosystem service and essential for carbon sequestration and biomass production. However, the intra-seasonal dynamics of tree height and stem diameter growth have been difficult to measure hampering the understanding of the interplay between these processes. Here, we investigated the feasibility of a laser scanning system in monitoring tree height development, aiming to study how tree height and stem diameter growth dynamics vary and interact, and how environmental variables explain the tree growth dynamics within a growing season. The experimental design consisted of 40 boreal trees equipped with dendrometers measuring changes in the stem diameter at 15-minutes intervals while a laser scanner fixed to a 35-meter tower was used to measure tree height near-daily during the monitoring period from May to mid-August 2021. We found that vertical changes in the tree-segmented point clouds enabled monitoring of tree height increment and investigation of the temporal dynamics of changes in tree height and stem diameter, when coupled with dendrometer measurements. The experiments revealed that, on average, height increment occurred ahead of diameter increment and deviated more towards the late season. Norway spruce showed more delayed diameter increment than Scots pine during the late season. Silver birch experienced diameter increment ahead of height increment. Based on the dendrometer measurements, we computed a radial change response function that aimed at characterizing the current state of stem diameter development, whether it was increasing or decreasing from its past state. When these radial change responses were compared against environmental variables, we found that the radial change response was mostly controlled by balance between precipitation and evapotranspiration, soil water content, minimum daily temperature, and vapor pressure deficit. Our findings support the utilization of laser scanning time series for measuring intra-seasonal changes in tree height and increase our understanding of the interactions between tree height and stem diameter growth processes.

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Yrttimaa T, Matsuzaki S, Kankare V, Junttila S, Saarinen N, Kukko A, Hyyppä J, Miura J, Vastaranta M: Assessing Forest Traversability for Autonomous Mobile Systems Using CloseRange Airborne Laser Scanning. In: Croatian Journal of Forest Engineering, vol. 45, no. 1, pp. 169–182, 2024, ISSN: 1845-5719, (Publisher Copyright: © 2023 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license.). (Type: Journal Article | Abstract | Links)

@article{a8c524ddc7fd4325a87533c32d8558a6,

title = {Assessing Forest Traversability for Autonomous Mobile Systems Using CloseRange Airborne Laser Scanning},

author = {Tuomas Yrttimaa and Shigemichi Matsuzaki and Ville Kankare and Samuli Junttila and Ninni Saarinen and Antero Kukko and Juha Hyyppä and Jun Miura and Mikko Vastaranta},

doi = {10.5552/crojfe.2024.2229},

issn = {1845-5719},

year  = {2024},

date = {2024-01-01},

journal = {Croatian Journal of Forest Engineering},

volume = {45},

number = {1},

pages = {169–182},

publisher = {FOREST FACULTY OF ZAGREB UNIVERSITY},

abstract = {Advances in sensor technology and computing performance has brought us into an era of digital forestry where a forest environment can be digitally replicated. At the same time, an increasing interest in the use of unmanned vehicles and other autonomous mobile systems (AMSs) in forest mapping and operations has emerged. However, a forest is an unstructured and rather complex environment for AMSs to operate in, and usually some kind of a priori information of traversability is required. The aim of this study was to assess forest traversability for AMSs using high-density airborne laser scanning (ALS) point clouds. It was assumed that such point clouds acquired from a helicopter flying at a low altitude can be used to characterise vegetation obstacles affecting forest traversability. A voxel-based vegetation occupancy analysis was carried out with the aim to detect open space to define traversable three-dimensional space. The experimental setup included seven sample plots (32x32 m) representing diverse boreal forest structures. Terrestrial laser scanning (TLS) was used for obtaining reference for vegetation occupancy. Comparison between ALS and TLS revealed an overall accuracy of 0.85-0.94 with a recall of 0.78-0.91 and a precision of 0.62-0.74 for ALS-based voxel classification for vegetation occupancy depending on forest structure. This implies that up to 91% of voxels assigned a classification >> occupied << based on the TLS could be correctly classified using the ALS, while up to 74% of voxels assigned a classification >> occupied << using the ALS were occupied based on the TLS. Density of low vegetation accounted for 83% of the variation in accuracy and precision. The feasibility of vegetation occupancy information to be used by an AMS for navigation was also demonstrated. It was assumed that the ALS data convey as sufficient information of AMS path planning as does the TLS data. The experiments showed that out of 1393 randomly generated paths based on empty space detected by the ALS, 72% were considered feasible when validated with the TLS data. The success rate in path planning varied from 0.54 to 0.92 between the sample plots and was seemingly affected by vegetation density that accounted for 53% of variation in success rate. Altogether, the demonstrated possibility to predefine forest traversability using remote sensing will support the use of AMSs in forestry.},

note = {Publisher Copyright: © 2023 by the authors. Submitted for possible open access publication under the terms and conditions of the Creative Commons Attribution (CC BY) license.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Close

Advances in sensor technology and computing performance has brought us into an era of digital forestry where a forest environment can be digitally replicated. At the same time, an increasing interest in the use of unmanned vehicles and other autonomous mobile systems (AMSs) in forest mapping and operations has emerged. However, a forest is an unstructured and rather complex environment for AMSs to operate in, and usually some kind of a priori information of traversability is required. The aim of this study was to assess forest traversability for AMSs using high-density airborne laser scanning (ALS) point clouds. It was assumed that such point clouds acquired from a helicopter flying at a low altitude can be used to characterise vegetation obstacles affecting forest traversability. A voxel-based vegetation occupancy analysis was carried out with the aim to detect open space to define traversable three-dimensional space. The experimental setup included seven sample plots (32x32 m) representing diverse boreal forest structures. Terrestrial laser scanning (TLS) was used for obtaining reference for vegetation occupancy. Comparison between ALS and TLS revealed an overall accuracy of 0.85-0.94 with a recall of 0.78-0.91 and a precision of 0.62-0.74 for ALS-based voxel classification for vegetation occupancy depending on forest structure. This implies that up to 91% of voxels assigned a classification >> occupied << based on the TLS could be correctly classified using the ALS, while up to 74% of voxels assigned a classification >> occupied << using the ALS were occupied based on the TLS. Density of low vegetation accounted for 83% of the variation in accuracy and precision. The feasibility of vegetation occupancy information to be used by an AMS for navigation was also demonstrated. It was assumed that the ALS data convey as sufficient information of AMS path planning as does the TLS data. The experiments showed that out of 1393 randomly generated paths based on empty space detected by the ALS, 72% were considered feasible when validated with the TLS data. The success rate in path planning varied from 0.54 to 0.92 between the sample plots and was seemingly affected by vegetation density that accounted for 53% of variation in success rate. Altogether, the demonstrated possibility to predefine forest traversability using remote sensing will support the use of AMSs in forestry.

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Turkulainen E, Honkavaara E, Näsi R, Oliveira R A, Hakala T, Junttila S, Karila K, Koivumäki N, Pelto-Arvo M, Tuviala J, Östersund M, Pölönen I, Lyytikäinen-Saarenmaa P: Comparison of Deep Neural Networks in the Classification of Bark Beetle-Induced Spruce Damage Using UAS Images. In: Remote Sensing, vol. 15, no. 20, pp. 4928, 2023, ISSN: 2072-4292. (Type: Journal Article | Links)

Forzieri G, Dutrieux L P, Elia A, Eckhardt B, Caudullo G, Taboada F A, Andriolo A, Balacenoiu F, Bastos A, Buzatu A, Dorado F C, Dobrovolny L, Duduman M, Fernandez-Carrillo A, Hernandez-Clemente R, Hornero A, Ionut S, Lombardero M J, Junttila S, Lukes P, Marianelli L, Mas H, Mlcousek M, Mugnai F, Netoiu C, Nikolov C, Olenici N, Olsson P, Paoli F, Paraschiv M, Patocka Z, Perez-Laorga E, Quero J L, Ruetschi M, Stroheker S, Nardi D, Ferencik J, Battisti A, Hartmann H, Nistor C, Cescatti A, Beck P S A: The Database of European Forest Insect and Disease Disturbances: Defid2. In: Global Change Biology, 2023, ISSN: 1354-1013. (Type: Journal Article | Abstract | Links)

@article{ebd38c1e26614237863162f94f052e3a,

title = {The Database of European Forest Insect and Disease Disturbances: Defid2},

author = {Giovanni Forzieri and Loic P. Dutrieux and Agata Elia and Bernd Eckhardt and Giovanni Caudullo and Flor Alvarez Taboada and Alessandro Andriolo and Flavius Balacenoiu and Ana Bastos and Andrei Buzatu and Fernando Castedo Dorado and Lumir Dobrovolny and Mihai-Leonard Duduman and Angel Fernandez-Carrillo and Rocio Hernandez-Clemente and Alberto Hornero and Savulescu Ionut and Maria J. Lombardero and Samuli Junttila and Petr Lukes and Leonardo Marianelli and Hugo Mas and Marek Mlcousek and Francesco Mugnai and Constantin Netoiu and Christo Nikolov and Nicolai Olenici and Per-Ola Olsson and Francesco Paoli and Marius Paraschiv and Zdenek Patocka and Eduardo Perez-Laorga and Jose Luis Quero and Marius Ruetschi and Sophie Stroheker and Davide Nardi and Jan Ferencik and Andrea Battisti and Henrik Hartmann and Constantin Nistor and Alessandro Cescatti and Pieter S. A. Beck},

doi = {10.1111/gcb.16912},

issn = {1354-1013},

year  = {2023},

date = {2023-08-22},

journal = {Global Change Biology},

publisher = {Wiley},

abstract = {Insect and disease outbreaks in forests are biotic disturbances that can profoundly alter ecosystem dynamics. In many parts of the world, these disturbance regimes are intensifying as the climate changes and shifts the distribution of species and biomes. As a result, key forest ecosystem services, such as carbon sequestration, regulation of water flows, wood production, protection of soils, and the conservation of biodiversity, could be increasingly compromised. Despite the relevance of these detrimental effects, there are currently no spatially detailed databases that record insect and disease disturbances on forests at the pan-European scale. Here, we present the new Database of European Forest Insect and Disease Disturbances (DEFID2). It comprises over 650,000 harmonized georeferenced records, mapped as polygons or points, of insects and disease disturbances that occurred between 1963 and 2021 in European forests. The records currently span eight different countries and were acquired through diverse methods (e.g., ground surveys, remote sensing techniques). The records in DEFID2 are described by a set of qualitative attributes, including severity and patterns of damage symptoms, agents, host tree species, climate-driven trigger factors, silvicultural practices, and eventual sanitary interventions. They are further complemented with a satellite-based quantitative characterization of the affected forest areas based on Landsat Normalized Burn Ratio time series, and damage metrics derived from them using the LandTrendr spectral-temporal segmentation algorithm (including onset, duration, magnitude, and rate of the disturbance), and possible interactions with windthrow and wildfire events. The DEFID2 database is a novel resource for many large-scale applications dealing with biotic disturbances. It offers a unique contribution to design networks of experiments, improve our understanding of ecological processes underlying biotic forest disturbances, monitor their dynamics, and enhance their representation in land-climate models. Further data sharing is encouraged to extend and improve the DEFID2 database continuously. The database is freely available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opend ata/FOREST/DISTU RBANCES/DEFID2/.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

Close

Insect and disease outbreaks in forests are biotic disturbances that can profoundly alter ecosystem dynamics. In many parts of the world, these disturbance regimes are intensifying as the climate changes and shifts the distribution of species and biomes. As a result, key forest ecosystem services, such as carbon sequestration, regulation of water flows, wood production, protection of soils, and the conservation of biodiversity, could be increasingly compromised. Despite the relevance of these detrimental effects, there are currently no spatially detailed databases that record insect and disease disturbances on forests at the pan-European scale. Here, we present the new Database of European Forest Insect and Disease Disturbances (DEFID2). It comprises over 650,000 harmonized georeferenced records, mapped as polygons or points, of insects and disease disturbances that occurred between 1963 and 2021 in European forests. The records currently span eight different countries and were acquired through diverse methods (e.g., ground surveys, remote sensing techniques). The records in DEFID2 are described by a set of qualitative attributes, including severity and patterns of damage symptoms, agents, host tree species, climate-driven trigger factors, silvicultural practices, and eventual sanitary interventions. They are further complemented with a satellite-based quantitative characterization of the affected forest areas based on Landsat Normalized Burn Ratio time series, and damage metrics derived from them using the LandTrendr spectral-temporal segmentation algorithm (including onset, duration, magnitude, and rate of the disturbance), and possible interactions with windthrow and wildfire events. The DEFID2 database is a novel resource for many large-scale applications dealing with biotic disturbances. It offers a unique contribution to design networks of experiments, improve our understanding of ecological processes underlying biotic forest disturbances, monitor their dynamics, and enhance their representation in land-climate models. Further data sharing is encouraged to extend and improve the DEFID2 database continuously. The database is freely available at https://jeodpp.jrc.ec.europa.eu/ftp/jrc-opend ata/FOREST/DISTU RBANCES/DEFID2/.

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Poyatos R, Fatecha B, Nelson J A, Flo V, Granda V, Cáceres M D, Anderegg W R L, Bittencourt P R L, Fisher R A, Junttila S, Konings A, Migliavacca M, Miralles D G, Novick K A, Rowland L, Zhang W, Mencuccini M, Martínez-Vilalta J: Quantifying water use resilience from sap flow data to better understand post-drought effects on tree functioning. In: 2023. (Type: Journal Article | Links)

Junttila S, Descals A, Filella I, Peñuelas J, Brandt M, Wigneron J, Vastaranta M: Vegetation optical depth reveals changes in ecosystem-level water stress for global forests. In: 2023. (Type: Journal Article | Links)

Calders K, Brede B, Newnham G, Culvenor D, Armston J, Bartholomeus H, Griebel A, Hayward J, Junttila S, Lau A, Levick S, Morrone R, Origo N, Pfeifer M, Verbesselt J, Herold M: StrucNet: a global network for automated vegetation structure monitoring. In: Remote Sensing in Ecology and Conservation, vol. 9, no. 5, pp. 587–598, 2023, ISSN: 2056-3485. (Type: Journal Article | Links)

Schiefer F, Schmidtlein S, Frick A, Frey J, Klinke R, Zielewska-Büttner K, Junttila S, Uhl A, Kattenborn T: UAV-based reference data for the prediction of fractional cover of standing deadwood from Sentinel time series. In: ISPRS Open Journal of Photogrammetry and Remote Sensing, vol. 8, pp. 100034, 2023, ISSN: 2667-3932. (Type: Journal Article | Links)

Kanerva H, Honkavaara E, Näsi R, Hakala T, Junttila S, Karila K, Koivumäki N, Oliveira R A, Pelto-Arvo M, Pölönen I, Tuviala J, Östersund M, Lyytikäinen-Saarenmaa P: Estimating Tree Health Decline Caused by Ips typographus L. from UAS RGB Images Using a Deep One-Stage Object Detection Neural Network. In: Remote Sensing, vol. 14, no. 24, pp. 6257, 2022, ISSN: 2072-4292. (Type: Journal Article | Links)

Imangholiloo M, Yrttimaa T, Mattsson T, Junttila S, Holopainen M, Saarinen N, Savolainen P, Hyyppä J, Vastaranta M: Adding single tree features and correcting edge tree effects enhance the characterization of seedling stands with single-photon airborne laser scanning. In: ISPRS Journal of Photogrammetry and Remote Sensing, vol. 191, pp. 129–142, 2022, ISSN: 0924-2716. (Type: Journal Article | Abstract | Links)

@article{00ca55244dd5490284ebd195b82340ea,

title = {Adding single tree features and correcting edge tree effects enhance the characterization of seedling stands with single-photon airborne laser scanning},

author = {Mohammad Imangholiloo and Tuomas Yrttimaa and Teppo Mattsson and Samuli Junttila and Marjut Holopainen and Ninni Saarinen and P. Savolainen and J. Hyyppä and Mikko Vastaranta},

doi = {10.1016/j.isprsjprs.2022.07.005},

issn = {0924-2716},

year  = {2022},

date = {2022-09-01},

journal = {ISPRS Journal of Photogrammetry and Remote Sensing},

volume = {191},

pages = {129–142},

publisher = {Elsevier Scientific Publ. Co},

abstract = {Silvicultural tending of seedling stands is important to producing quality timber. However, it is challenging to allocate where and when to apply these silvicultural tending actions. Here, we tested and evaluated two methodological modifications of the ordinary area-based approach (ABAOrdinary) that could be utilized in the airborne laser scanning-based forest inventories and especially seedling stand characterization. We hypothesize that ABA with added individual tree detection-derived features (ABAITD) or correcting edge-tree effects (ABAEdge) would display improved performance in estimating the tree density and mean tree height of seedling stands. We tested this hypothesis using single-photon laser (SPL) and linear-mode laser (LML) scanning data covering 89 sample plots.The obtained results supported the hypothesis as the methodological modifications improved seedling stand characterization. Compared to the performance of ABAordinary, relative bias in tree density estimation decreased from 17.2% to 10.1% when we applied ABAITD. In the case of mean height estimation, the relative root mean square error decreased from 19.5% to 16.3% when we applied ABAEdgeITD. The SPL technology provided practically comparable or, in some cases, enhanced performance in seedling stand characterization when compared to conventional LML technology. Based on the obtained findings, it seems that the tested methodological improvements should be carefully considered when ALS-based inventories supporting forest management and silvicultural decision-making are developed further.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

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Liang X, Kukko A, Balenovic I, Saarinen N, Junttila S, Kankare V, Holopainen M, Mokros M, Surovy P, Kaartinen H, Jurjevic L, Honkavaara E, Nasi R, Liu J, Hollaus M, Tian J, Yu X, Pan J, Cai S, Virtanen J, Wang Y, Hyyppa J: Close-Range Remote Sensing of Forests: The State of the Art, Challenges, and Opportunities for Systems and Data Acquisitions. In: Ieee geoscience and remote sensing magazine, vol. 10, no. 3, pp. 32–71, 2022, ISSN: 2473-2397. (Type: Journal Article | Links)

Yrttimaa T, Luoma V, Saarinen N, Kankare E, Junttila S, Holopainen M, Hyyppa J, Vastaranta M: Exploring tree growth allometry using two-date terrestrial laser scanning. In: Forest Ecology and Management, vol. 518, 2022, ISSN: 0378-1127. (Type: Journal Article | Abstract | Links)

@article{f64a38adb77c4f8d996194587f1d93d1,

title = {Exploring tree growth allometry using two-date terrestrial laser scanning},

author = {Tuomas Yrttimaa and Ville Luoma and Ninni Saarinen and Elina Kankare and Samuli Junttila and Markus Holopainen and Juha Hyyppa and Mikko Vastaranta},

doi = {10.1016/j.foreco.2022.120303},

issn = {0378-1127},

year  = {2022},

date = {2022-08-15},

journal = {Forest Ecology and Management},

volume = {518},

publisher = {Elsevier Scientific Publ. Co},

abstract = {Tree growth is a physio-ecological phenomena of high interest among researchers across disciplines. Observing changes in tree characteristics has conventionally required either repeated measurements of the characteristics of living trees, retrospective measurements of destructively sampled trees, or modelling. The use of close-range sensing techniques such as terrestrial laser scanning (TLS) has enabled non-destructive approaches to reconstruct the three-dimensional (3D) structure of trees and tree communities in space and time. This study aims at improving the understanding of tree allometry in general and interactions between tree growth and its neighbourhood in particular by using two-date point clouds. We investigated how variation in the increments in basal area at the breast height (Delta g(1.3)), basal area at height corresponding to 60% of tree height (Delta g(0)(6h)), and volume of the stem section below 50% of tree height (Delta v(05h) ) can be explained with TLS point cloud-based attributes characterizing the spatiotemporal structure of a tree crown and crown neighbourhood, entailing the competitive status of a tree. The analyses were based on 218 trees on 16 sample plots whose 3D characteristics were obtained at the beginning (2014, T1) and at the end of the monitoring period (2019, T2) from multi-scan TLS point clouds using automatic point cloud processing methods. The results of this study showed that, within certain tree communities, strong relationships (vertical bar r vertical bar > 0.8) were observed between increments in the stem dimensions and the attributes characterizing crown structure and competition. Most often, attributes characterizing the competitive status of a tree, and the crown structure at T1, were the most important attributes to explain variation in the increments of stem dimensions. Linear mixed-effect modelling showed that single attributes could explain up to 35-60% of the observed variation in Delta g(1.3), Delta g(0)(6h) and Delta V-0(5h), depending on the tree species. This tree-level evidence of the allometric relationship between stem growth and crown dynamics can further be used to justify landscape-level analyses based on airborne remote sensing technologies to monitor stem growth through the structure and development of crown structure. This study contributes to the existing knowledge by showing that laser-based close-range sensing is a feasible technology to provide 3D characterization of stem and crown structure, enabling one to quantify structural changes and the competitive status of trees for improved understanding of the underlying growth processes.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

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Tree growth is a physio-ecological phenomena of high interest among researchers across disciplines. Observing changes in tree characteristics has conventionally required either repeated measurements of the characteristics of living trees, retrospective measurements of destructively sampled trees, or modelling. The use of close-range sensing techniques such as terrestrial laser scanning (TLS) has enabled non-destructive approaches to reconstruct the three-dimensional (3D) structure of trees and tree communities in space and time. This study aims at improving the understanding of tree allometry in general and interactions between tree growth and its neighbourhood in particular by using two-date point clouds. We investigated how variation in the increments in basal area at the breast height (Delta g(1.3)), basal area at height corresponding to 60% of tree height (Delta g(0)(6h)), and volume of the stem section below 50% of tree height (Delta v(05h) ) can be explained with TLS point cloud-based attributes characterizing the spatiotemporal structure of a tree crown and crown neighbourhood, entailing the competitive status of a tree. The analyses were based on 218 trees on 16 sample plots whose 3D characteristics were obtained at the beginning (2014, T1) and at the end of the monitoring period (2019, T2) from multi-scan TLS point clouds using automatic point cloud processing methods. The results of this study showed that, within certain tree communities, strong relationships (vertical bar r vertical bar > 0.8) were observed between increments in the stem dimensions and the attributes characterizing crown structure and competition. Most often, attributes characterizing the competitive status of a tree, and the crown structure at T1, were the most important attributes to explain variation in the increments of stem dimensions. Linear mixed-effect modelling showed that single attributes could explain up to 35-60% of the observed variation in Delta g(1.3), Delta g(0)(6h) and Delta V-0(5h), depending on the tree species. This tree-level evidence of the allometric relationship between stem growth and crown dynamics can further be used to justify landscape-level analyses based on airborne remote sensing technologies to monitor stem growth through the structure and development of crown structure. This study contributes to the existing knowledge by showing that laser-based close-range sensing is a feasible technology to provide 3D characterization of stem and crown structure, enabling one to quantify structural changes and the competitive status of trees for improved understanding of the underlying growth processes.

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Junttila S, Hölttä T, Salmon Y, Filella I, Peñuelas J: A Novel Method to Simultaneously Measure Leaf Gas Exchange and Water Content. In: Remote Sensing, vol. 14, no. 15, pp. 3693, 2022, ISSN: 2072-4292. (Type: Journal Article | Links)

Junttila S, Hölttä T, Saarinen N, Kankare V, Yrttimaa T, Hyyppa J, Vastaranta M: Close-range hyperspectral spectroscopy reveals leaf water content dynamics. In: Remote Sensing of Environment, vol. 277, 2022, ISSN: 0034-4257. (Type: Journal Article | Abstract | Links)

@article{cacf67bf4fbd44d1817f8c6f5f24d84d,

title = {Close-range hyperspectral spectroscopy reveals leaf water content dynamics},

author = {Samuli Junttila and Tiina Hölttä and Ninni Saarinen and Ville Kankare and Tuomas Yrttimaa and J. Hyyppa and Mikko Vastaranta},

doi = {10.1016/j.rse.2022.113071},

issn = {0034-4257},

year  = {2022},

date = {2022-08-01},

journal = {Remote Sensing of Environment},

volume = {277},

publisher = {EXCERPTA MEDICA INC-ELSEVIER SCIENCE INC},

abstract = {Water plays a crucial role in maintaining plant functionality and drives many ecophysiological processes. The distribution of water resources is in a continuous change due to global warming affecting the productivity of ecosystems around the globe, but there is a lack of non-destructive methods capable of continuous monitoring of plant and leaf water content that would help us in understanding the consequences of the redistribution of water. We studied the utilization of novel small hyperspectral sensors in the 1350-1650 nm and 2000-2450 nm spectral ranges in non-destructive estimation of leaf water content in laboratory and field conditions. We found that the sensors captured up to 96% of the variation in equivalent water thickness (EWT, g/m(2)) and up to 90% of the variation in relative water content (RWC). Further tests were done with an indoor plant (Dracaena marginate Lem.) by continuously measuring leaf spectra while drought conditions developed, which revealed detailed diurnal dynamics of leaf water content. The laboratory findings were supported by field measurements, where repeated leaf spectra measurements were in fair agreement (R-2 = 0.70) with RWC and showed similar diurnal dynamics. The estimation of leaf mass per area (LMA) using leaf spectra was investigated as a pathway to improved RWC estimation, but no significant improvement was found. We conclude that close-range hyper spectral spectroscopy can provide a novel tool for continuous measurement of leaf water content at the single leaf level and help us to better understand plant responses to varying environmental conditions.},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

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Junttila S, Campos M, Hölttä T, Lindfors L, Issaoui A E, Vastaranta M, Hyyppä H, Puttonen E: Tree Water Status Affects Tree Branch Position. In: Forests, vol. 13, no. 5, pp. 728, 2022, ISSN: 1999-4907. (Type: Journal Article | Links)

Vastaranta M, Wulder M A, Hamari J, Hyyppä J, Junttila S: Forest Data to Insights and Experiences Using Gamification. In: Frontiers in Forests and Global Change, vol. 5, 2022, ISSN: 2624-893X. (Type: Journal Article | Links)

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