Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS

Chapter Contents (Back)
Forest. Terrestrial Laser Scanner. TLS. Laser.

Henning, J.G.[Jason G.], Radtke, P.J.[Philip J.],
Multiview range-image registration for forested scenes using explicitly-matched tie points estimated from natural surfaces,
PandRS(63), No. 1, January 2008, pp. 68-83.
Elsevier DOI 0711
Alignment; Terrestrial laser scanning; Canopy structure; Point cloud; Ground-based lidar; Stem map; Stem profile; Digital terrain model BibRef

van der Zande, D., Stuckens, J., Verstraeten, W., Muys, B., Coppin, P.,
Assessment of Light Environment Variability in Broadleaved Forest Canopies Using Terrestrial Laser Scanning,
RS(2), No. 6, June 2010, pp. 1564-1574.
DOI Link 1203

Moskal, L.M., Zheng, G.,
Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest,
RS(4), No. 1, January 2012, pp. 1-20.
DOI Link 1203

Zheng, G., Moskal, L.M.,
Computational-Geometry-Based Retrieval of Effective Leaf Area Index Using Terrestrial Laser Scanning,
GeoRS(50), No. 10, October 2012, pp. 3958-3969.

Zheng, G., Ma, L., He, W., Eitel, J.U.H., Moskal, L.M., Zhang, Z.,
Assessing the Contribution of Woody Materials to Forest Angular Gap Fraction and Effective Leaf Area Index Using Terrestrial Laser Scanning Data,
GeoRS(54), No. 3, March 2016, pp. 1475-1487.
Distance measurement BibRef

Zheng, G., Moskal, L.M., Kim, S.H.,
Retrieval of Effective Leaf Area Index in Heterogeneous Forests With Terrestrial Laser Scanning,
GeoRS(51), No. 2, February 2013, pp. 777-786.

Pirotti, F.[Francesco], Guarnieri, A.[Alberto], Vettore, A.[Antonio],
Ground filtering and vegetation mapping using multi-return terrestrial laser scanning,
PandRS(76), No. 1, February 2013, pp. 56-63.
Elsevier DOI 1301
Earlier: A2, A1, A3:
Comparison Of Discrete Return And Waveform Terrestrial Laser Scanning For Dense Vegetation Filtering,
DOI Link 1209
Earlier: A1, A2, A3:
Vegetation Characteristics Using Multi-Return Terrestrial Laser Scanner,
DOI Link 1109
Terrestrial laser scanning; Vegetation mapping; Spatial classification; Point cloud processing; DEM/DTM BibRef

Ramirez, F.A.[F. Alberto], Armitage, R.P.[Richard P.], Danson, F.M.[F. Mark],
Testing the Application of Terrestrial Laser Scanning to Measure Forest Canopy Gap Fraction,
RS(5), No. 6, 2013, pp. 3037-3056.
DOI Link 1307

Hancock, S., Gaulton, R., Danson, F.M.,
Angular Reflectance of Leaves With a Dual-Wavelength Terrestrial Lidar and Its Implications for Leaf-Bark Separation and Leaf Moisture Estimation,
GeoRS(55), No. 6, June 2017, pp. 3084-3090.
Laser radar, Measurement by laser beam, Scattering, Surface emitting lasers, Vegetation mapping, Wavelength measurement, Laser radar, remote sensing, technology assessment, vegetation BibRef

Pueschel, P.[Pyare], Newnham, G.[Glenn], Hill, J.[Joachim],
Retrieval of Gap Fraction and Effective Plant Area Index from Phase-Shift Terrestrial Laser Scans,
RS(6), No. 3, 2014, pp. 2601-2627.
DOI Link 1404
Gaps in the canopy. BibRef

Othmani, A.[Ahlem], Voon, L.F.C.L.Y.[Lew F.C. Lew Yan], Stolz, C.[Christophe], Piboule, A.[Alexandre],
Single tree species classification from Terrestrial Laser Scanning data for forest inventory,
PRL(34), No. 16, 2013, pp. 2144-2150.
Elsevier DOI 1310
Single tree species classification BibRef

Othmani, A.[Ahlem], Lomenie, N.[Nicolas], Piboule, A.[Alexandre], Stolz, C.[Christophe], Voon, L.F.C.L.Y.[Lew F.C. Lew Yan],
Region-based segmentation on depth images from a 3D reference surface for tree species recognition,
Forest inventory BibRef

Gupta, V.[Vaibhav], Reinke, K.J.[Karin J.], Jones, S.D.[Simon D.], Wallace, L.[Luke], Holden, L.[Lucas],
Assessing Metrics for Estimating Fire Induced Change in the Forest Understorey Structure Using Terrestrial Laser Scanning,
RS(7), No. 6, 2015, pp. 8180.
DOI Link 1507

Wallace, L.[Luke], Gupta, V.[Vaibhav], Reinke, K.J.[Karin J.], Jones, S.D.[Simon D.],
An Assessment of Pre- and Post Fire Near Surface Fuel Hazard in an Australian Dry Sclerophyll Forest Using Point Cloud Data Captured Using a Terrestrial Laser Scanner,
RS(8), No. 8, 2016, pp. 679.
DOI Link 1609

Ma, L., Zheng, G., Eitel, J.U.H., Moskal, L.M., He, W., Huang, H.,
Improved Salient Feature-Based Approach for Automatically Separating Photosynthetic and Nonphotosynthetic Components Within Terrestrial Lidar Point Cloud Data of Forest Canopies,
GeoRS(54), No. 2, February 2016, pp. 679-696.
Accuracy BibRef

Liang, X.L.[Xin-Lian], Kankare, V.[Ville], Hyyppä, J.[Juha], Wang, Y.S.[Yun-Sheng], Kukko, A.[Antero], Haggrén, H.[Henrik], Yu, X.W.[Xiao-Wei], Kaartinen, H.[Harri], Jaakkola, A.[Anttoni], Guan, F.Y.[Feng-Ying], Holopainen, M.[Markus], Vastaranta, M.[Mikko],
Terrestrial laser scanning in forest inventories,
PandRS(115), No. 1, 2016, pp. 63-77.
Elsevier DOI 1604
Forest inventory BibRef

Liang, X.L.[Xin-Lian], Hyyppä, J.[Juha], Kaartinen, H.[Harri], Lehtomäki, M.[Matti], Pyörälä, J.[Jiri], Pfeifer, N.[Norbert], Holopainen, M.[Markus], Brolly, G.[Gábor], Francesco, P.[Pirotti], Hackenberg, J.[Jan], Huang, H.[Huabing], Jo, H.W.[Hyun-Woo], Katoh, M.[Masato], Liu, L.X.[Lu-Xia], Mokroš, M.[Martin], Morel, J.[Jules], Olofsson, K.[Kenneth], Poveda-Lopez, J.[Jose], Trochta, J.[Jan], Wang, D.[Di], Wang, J.H.[Jin-Hu], Xi, Z.X.[Zhou-Xi], Yang, B.S.[Bi-Sheng], Zheng, G.[Guang], Kankare, V.[Ville], Luoma, V.[Ville], Yu, X.W.[Xiao-Wei], Chen, L.[Liang], Vastaranta, M.[Mikko], Saarinen, N.[Ninni], Wang, Y.S.[Yun-Sheng],
International benchmarking of terrestrial laser scanning approaches for forest inventories,
PandRS(144), 2018, pp. 137-179.
Elsevier DOI 1809
Benchmarking, State-of-the-art, Forest, Modeling, Point cloud, Terrestrial laser scanning, TLS BibRef

Saarinen, N.[Ninni], Kankare, V.[Ville], Vastaranta, M.[Mikko], Luoma, V.[Ville], Pyörälä, J.[Jiri], Tanhuanpää, T.[Topi], Liang, X.[Xinlian], Kaartinen, H.[Harri], Kukko, A.[Antero], Jaakkola, A.[Anttoni], Yu, X.W.[Xiao-Wei], Holopainen, M.[Markus], Hyyppä, J.[Juha],
Feasibility of Terrestrial laser scanning for collecting stem volume information from single trees,
PandRS(123), No. 1, 2017, pp. 140-158.
Elsevier DOI 1612
Forest mensuration BibRef

Kelbe, D., van Aardt, J., Romanczyk, P., van Leeuwen, M., Cawse-Nicholson, K.,
Marker-Free Registration of Forest Terrestrial Laser Scanner Data Pairs With Embedded Confidence Metrics,
GeoRS(54), No. 7, July 2016, pp. 4314-4330.
Imaging BibRef

Kelbe, D., van Aardt, J., Romanczyk, P., van Leeuwen, M., Cawse-Nicholson, K.,
Multiview Marker-Free Registration of Forest Terrestrial Laser Scanner Data With Embedded Confidence Metrics,
GeoRS(55), No. 2, February 2017, pp. 729-741.
forestry BibRef

Jiang, Y.T.[Yi-Tong], Weng, Q.H.[Qi-Hao], Speer, J.H.[James H.], Baker, S.[Steven],
Estimating Tree Frontal Area in Urban Areas Using Terrestrial LiDAR Data,
RS(8), No. 5, 2016, pp. 401.
DOI Link 1606

Polewski, P.[Przemyslaw], Yao, W.[Wei], Heurich, M.[Marco], Krzystek, P.[Peter], Stilla, U.[Uwe],
A voting-based statistical cylinder detection framework applied to fallen tree mapping in terrestrial laser scanning point clouds,
PandRS(129), No. 1, 2017, pp. 118-130.
Elsevier DOI 1706
TLS BibRef

Guo, X.X.[Xian-Xian], Wang, L.[Le], Tian, J.Y.[Jin-Yan], Yin, D.M.[Da-Meng], Shi, C.[Chen], Nie, S.[Sheng],
Vegetation Horizontal Occlusion Index (VHOI) from TLS and UAV Image to Better Measure Mangrove LAI,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Rehush, N.[Nataliia], Abegg, M.[Meinrad], Waser, L.T.[Lars T.], Brändli, U.B.[Urs-Beat],
Identifying Tree-Related Microhabitats in TLS Point Clouds Using Machine Learning,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Xi, Z.X.[Zhou-Xin], Hopkinson, C.[Chris], Chasmer, L.[Laura],
Filtering Stems and Branches from Terrestrial Laser Scanning Point Clouds Using Deep 3-D Fully Convolutional Networks,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
LIDAR point clouds in forest. BibRef

Frey, J.[Julian], Joa, B.[Bettina], Schraml, U.[Ulrich], Koch, B.[Barbara],
Same Viewpoint Different Perspectives: A Comparison of Expert Ratings with a TLS Derived Forest Stand Structural Complexity Index,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905

Liu, J.[Jing], Skidmore, A.K.[Andrew K.], Wang, T.J.[Tie-Jun], Zhu, X.[Xi], Premier, J.[Joe], Heurich, M.[Marco], Beudert, B.[Burkhard], Jones, S.[Simon],
Variation of leaf angle distribution quantified by terrestrial LiDAR in natural European beech forest,
PandRS(148), 2019, pp. 208-220.
Elsevier DOI 1901
Leaf inclination, Leaf inclination distribution function, Leaf angle distribution, Variation, European beech BibRef

Liu, J.[Jing], Wang, T.J.[Tie-Jun], Skidmore, A.K.[Andrew K.], Jones, S.[Simon], Heurich, M.[Marco], Beudert, B.[Burkhard], Premier, J.[Joe],
Comparison of terrestrial LiDAR and digital hemispherical photography for estimating leaf angle distribution in European broadleaf beech forests,
PandRS(158), 2019, pp. 76-89.
Elsevier DOI 1912
Leaf inclination, Leaf orientation, Leaf angle distribution, Terrestrial LiDAR, Digital hemispherical photography, Gap fraction BibRef

Xu, Q.F.[Qiang-Fa], Cao, L.[Lin], Xue, L.F.[Lian-Feng], Chen, B.Q.[Bang-Qian], An, F.[Feng], Yun, T.[Ting],
Extraction of Leaf Biophysical Attributes Based on a Computer Graphic-based Algorithm Using Terrestrial Laser Scanning Data,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901

Huo, L.N.[Lang-Ning], Zhang, X.L.[Xiao-Li],
A new method of equiangular sectorial voxelization of single-scan terrestrial laser scanning data and its applications in forest defoliation estimation,
PandRS(151), 2019, pp. 302-312.
Elsevier DOI 1904
Single-scan TLS, Voxelization, Point density, Defoliation, Regression BibRef

Yrttimaa, T.[Tuomas], Saarinen, N.[Ninni], Kankare, V.[Ville], Liang, X.[Xinlian], Hyyppä, J.[Juha], Holopainen, M.[Markus], Vastaranta, M.[Mikko],
Investigating the Feasibility of Multi-Scan Terrestrial Laser Scanning to Characterize Tree Communities in Southern Boreal Forests,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907

Calders, K.[Kim], Schnitzer, S.A.[Stefan A.], Verbeeck, H.[Hans],
Semi-automatic extraction of liana stems from terrestrial LiDAR point clouds of tropical rainforests,
PandRS(154), 2019, pp. 114-126.
Elsevier DOI 1907
Automated liana extraction, Lianas, Terrestial LiDAR, Machine learning, Python package, Tropical forests BibRef

Schneider, R.[Robert], Calama, R.[Rafael], Martin-Ducup, O.[Olivier],
Understanding Tree-to-Tree Variations in Stone Pine (Pinus pinea L.) Cone Production Using Terrestrial Laser Scanner,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001

Wu, B.X.[Bing-Xiao], Zheng, G.[Guang], Chen, Y.[Yang],
An Improved Convolution Neural Network-Based Model for Classifying Foliage and Woody Components from Terrestrial Laser Scanning Data,
RS(12), No. 6, 2020, pp. xx-yy.
DOI Link 2003

Shao, J.[Jie], Zhang, W.[Wuming], Mellado, N.[Nicolas], Wang, N.[Nan], Jin, S.[Shuangna], Cai, S.S.[Shang-Shu], Luo, L.[Lei], Lejemble, T.[Thibault], Yan, G.J.[Guang-Jian],
SLAM-aided forest plot mapping combining terrestrial and mobile laser scanning,
PandRS(163), 2020, pp. 214-230.
Elsevier DOI 2005
Forest mapping, LiDAR, SLAM, Single-scan TLS, MLS BibRef

LaRue, E.A.[Elizabeth A.], Wagner, F.W.[Franklin W.], Fei, S.[Songlin], Atkins, J.W.[Jeff W.], Fahey, R.T.[Robert T.], Gough, C.M.[Christopher M.], Hardiman, B.S.[Brady S.],
Compatibility of Aerial and Terrestrial LiDAR for Quantifying Forest Structural Diversity,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005

Wang, D.[Di],
Unsupervised semantic and instance segmentation of forest point clouds,
PandRS(165), 2020, pp. 86-97.
Elsevier DOI 2006
Terrestrial LiDAR, Tree isolation, Component classification, Segmentation, Superpoint graph BibRef

Yrttimaa, T.[Tuomas], Luoma, V.[Ville], Saarinen, N.[Ninni], Kankare, V.[Ville], Junttila, S.[Samuli], Holopainen, M.[Markus], Hyyppä, J.[Juha], Vastaranta, M.[Mikko],
Structural Changes in Boreal Forests Can Be Quantified Using Terrestrial Laser Scanning,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009

Yrttimaa, T.[Tuomas], Saarinen, N.[Ninni], Kankare, V.[Ville], Hynynen, J.[Jari], Huuskonen, S.[Saija], Holopainen, M.[Markus], Hyyppä, J.[Juha], Vastaranta, M.[Mikko],
Performance of terrestrial laser scanning to characterize managed Scots pine (Pinus sylvestris L.) stands is dependent on forest structural variation,
PandRS(168), 2020, pp. 277 - 287.
Elsevier DOI 2009
LiDAR, Remote sensing, Forest inventory, Point cloud, Close-range, Forest management BibRef

Terryn, L.[Louise], Calders, K.[Kim], Disney, M.[Mathias], Origo, N.[Niall], Malhi, Y.[Yadvinder], Newnham, G.[Glenn], Raumonen, P.[Pasi], Åkerblom, M.[Markku], Verbeeck, H.[Hans],
Tree species classification using structural features derived from terrestrial laser scanning,
PandRS(168), 2020, pp. 170 - 181.
Elsevier DOI 2009
Quantitative structure model, Structural tree features, Terrestrial laser scanning, Tree species classification, Machine learning classifiers BibRef

Xi, Z.[Zhouxin], Hopkinson, C.[Chris], Rood, S.B.[Stewart B.], Peddle, D.R.[Derek R.],
See the forest and the trees: Effective machine and deep learning algorithms for wood filtering and tree species classification from terrestrial laser scanning,
PandRS(168), 2020, pp. 1 - 16.
Elsevier DOI 2009
Tree species classification, 3D classification, Deep learning, Forests, Terrestrial laser scanning, LiDAR BibRef

Park, T.[Taejin],
Potential Lidar Height, Intensity, and Ratio Parameters for Plot Dominant Species Discrimination and Volume Estimation,
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010

Li, L., Mu, X., Soma, M., Wan, P., Qi, J., Hu, R., Zhang, W., Tong, Y., Yan, G.,
An Iterative-Mode Scan Design of Terrestrial Laser Scanning in Forests for Minimizing Occlusion Effects,
GeoRS(59), No. 4, April 2021, pp. 3547-3566.
Vegetation, Indexes, Forestry, Estimation, Measurement by laser beam, Laser radar, Nickel, Forest inventory, occlusion effect, scan design, visibility analysis BibRef

Seidel, D.[Dominik], Annighöfer, P.[Peter], Ammer, C.[Christian], Ehbrecht, M.[Martin], Willim, K.[Katharina], Bannister, J.[Jan], Soto, D.P.[Daniel P.],
Quantifying Understory Complexity in Unmanaged Forests Using TLS and Identifying Some of Its Major Drivers,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104

Camarretta, N.[Nicolò], Harrison, P.A.[Peter A.], Lucieer, A.[Arko], Potts, B.M.[Brad M.], Davidson, N.[Neil], Hunt, M.[Mark],
Handheld Laser Scanning Detects Spatiotemporal Differences in the Development of Structural Traits among Species in Restoration Plantings,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105

Song, J.L.[Jin-Ling], Zhu, X.[Xiao], Qi, J.B.[Jian-Bo], Pang, Y.[Yong], Yang, L.[Lei], Yu, L.H.[Li-Hong],
A Method for Quantifying Understory Leaf Area Index in a Temperate Forest through Combining Small Footprint Full-Waveform and Point Cloud LiDAR Data,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108

Ge, X.M.[Xu-Ming], Zhu, Q.[Qing],
Target-based automated matching of multiple terrestrial laser scans for complex forest scenes,
PandRS(179), 2021, pp. 1-13.
Elsevier DOI 2108
Point clouds, Forest, Registration, Target-based, Multiple scans BibRef

Arseniou, G.[Georgios], MacFarlane, D.W.[David W.], Seidel, D.[Dominik],
Woody Surface Area Measurements with Terrestrial Laser Scanning Relate to the Anatomical and Structural Complexity of Urban Trees,
RS(13), No. 16, 2021, pp. xx-yy.
DOI Link 2109

Abegg, M.[Meinrad], Boesch, R.[Ruedi], Schaepman, M.E.[Michael E.], Morsdorf, F.[Felix],
Impact of Beam Diameter and Scanning Approach on Point Cloud Quality of Terrestrial Laser Scanning in Forests,
GeoRS(59), No. 10, October 2021, pp. 8153-8167.
Laser beams, Forestry, Measurement by laser beam, Surface emitting lasers, stem diameter distribution BibRef

Panagiotidis, D.[Dimitrios], Abdollahnejad, A.[Azadeh],
Reliable Estimates of Merchantable Timber Volume from Terrestrial Laser Scanning,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109

Alvites, C.[Cesar], Santopuoli, G.[Giovanni], Hollaus, M.[Markus], Pfeifer, N.[Norbert], Maesano, M.[Mauro], Moresi, F.V.[Federico Valerio], Marchetti, M.[Marco], Lasserre, B.[Bruno],
Terrestrial Laser Scanning for Quantifying Timber Assortments from Standing Trees in a Mixed and Multi-Layered Mediterranean Forest,
RS(13), No. 21, 2021, pp. xx-yy.
DOI Link 2112

Xu, S.[Sheng], Li, X.[Xin], Yun, J.Y.[Jia-Yan], Xu, S.S.[Shan-Shan],
An Effectively Dynamic Path Optimization Approach for the Tree Skeleton Extraction from Portable Laser Scanning Point Clouds,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201

Dai, W.X.[Wen-Xia], Guan, Q.F.[Qing-Feng], Cai, S.S.[Shang-Shu], Liu, R.D.[Run-Dong], Chen, R.[Ruibo], Liu, Q.[Qing], Chen, C.[Chao], Dong, Z.[Zhen],
A Comparison of the Performances of Unmanned-Aerial-Vehicle (UAV) and Terrestrial Laser Scanning for Forest Plot Canopy Cover Estimation in Pinus massoniana Forests,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203

Sferlazza, S.[Sebastiano], Maltese, A.[Antonino], Dardanelli, G.[Gino], Veca, D.S.L.M.[Donato Salvatore La Mela],
Optimizing the Sampling Area across an Old-Growth Forest via UAV-Borne Laser Scanning, GNSS, and Radial Surveying,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204

Wang, M.[Meilian], Wong, M.S.[Man Sing], Abbas, S.[Sawaid],
Tropical Species Classification with Structural Traits Using Handheld Laser Scanning Data,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205

Xie, Y.Y.[Yu-Yang], Yang, T.[Tao], Wang, X.F.[Xiao-Feng], Chen, X.[Xi], Pang, S.X.[Shu-Xin], Hu, J.[Juan], Wang, A.X.[An-Xian], Chen, L.[Ling], Shen, Z.[Zehao],
Applying a Portable Backpack Lidar to Measure and Locate Trees in a Nature Forest Plot: Accuracy and Error Analyses,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205

Liu, B.J.[Bing-Jie], Chen, S.[Shuxin], Huang, H.G.[Hua-Guo], Tian, X.[Xin],
Tree Species Classification of Backpack Laser Scanning Data Using the PointNet++ Point Cloud Deep Learning Method,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208

Liu, B.J.[Bing-Jie], Huang, H.G.[Hua-Guo], Su, Y.[Yong], Chen, S.[Shuxin], Li, Z.Y.[Zeng-Yuan], Chen, E.[Erxue], Tian, X.[Xin],
Tree Species Classification Using Ground-Based LiDAR Data by Various Point Cloud Deep Learning Methods,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212

Vandendaele, B.[Bastien], Martin-Ducup, O.[Olivier], Fournier, R.A.[Richard A.], Pelletier, G.[Gaetan], Lejeune, P.[Philippe],
Mobile Laser Scanning for Estimating Tree Structural Attributes in a Temperate Hardwood Forest,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209

Bobrowski, R.[Rogério], Winczek, M.[Monika], Silva, L.P.[Lucas Polo], Cuchi, T.[Tarik], Szostak, M.[Marta], Wezyk, P.[Piotr],
Promising Uses of the iPad Pro Point Clouds: The Case of the Trunk Flare Diameter Estimation in the Urban Forest,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209

Martínez-Rodrigo, R.[Raquel], Gómez, C.[Cristina], Toraño-Caicoya, A.[Astor], Bohnhorst, L.[Luke], Uhl, E.[Enno], Águeda, B.[Beatriz],
Stand Structural Characteristics Derived from Combined TLS and Landsat Data Support Predictions of Mushroom Yields in Mediterranean Forest,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210

Ronoud, G.[Ghasem], Poorazimy, M.[Maryam], Yrttimaa, T.[Tuomas], Luoma, V.[Ville], Huuskonen, S.[Saija], Hynynen, J.[Jari], Hyyppä, J.[Juha], Saarinen, N.[Ninni], Kankare, V.[Ville], Vastaranta, M.[Mikko],
Terrestrial Laser Scanning in Assessing the Effect of Different Thinning Treatments on the Competition of Scots Pine (Pinus sylvestris L.) Forests,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211

Batchelor, J.L.[Jonathan L.], Wilson, T.M.[Todd M.], Olsen, M.J.[Michael J.], Ripple, W.J.[William J.],
New Structural Complexity Metrics for Forests from Single Terrestrial Lidar Scans,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301

Olofsson, K.[Kenneth], Holmgren, J.[Johan],
Stem Quality Estimates Using Terrestrial Laser Scanning Voxelized Data and a Voting-Based Branch Detection Algorithm,
RS(15), No. 8, 2023, pp. 2082.
DOI Link 2305

Xu, Z.Z.[Zhuang-Zhi], Shen, X.[Xin], Cao, L.[Lin],
Extraction of Forest Structural Parameters by the Comparison of Structure from Motion (SfM) and Backpack Laser Scanning (BLS) Point Clouds,
RS(15), No. 8, 2023, pp. 2144.
DOI Link 2305

Wielgosz, M.[Maciej], Puliti, S.[Stefano], Wilkes, P.[Phil], Astrup, R.[Rasmus],
Point2Tree(P2T): Framework for Parameter Tuning of Semantic and Instance Segmentation Used with Mobile Laser Scanning Data in Coniferous Forest,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308

Chen, C.[Chao], Zhou, L.[Lv], Li, X.J.[Xue-Jian], Zhao, Y.[Yinyin], Yu, J.[Jiacong], Lv, L.[Lujin], Du, H.Q.[Hua-Qiang],
Optimizing the Spatial Structure of Metasequoia Plantation Forest Based on UAV-LiDAR and Backpack-LiDAR,
RS(15), No. 16, 2023, pp. 4090.
DOI Link 2309

Schindler, Z.[Zoe], Larysch, E.[Elena], Frey, J.[Julian], Sheppard, J.P.[Jonathan P.], Obladen, N.[Nora], Kröner, K.[Katja], Seifert, T.[Thomas], Morhart, C.[Christopher],
From Dawn to Dusk: High-Resolution Tree Shading Model Based on Terrestrial LiDAR Data,
RS(16), No. 12, 2024, pp. 2189.
DOI Link 2406

Sofia, S., Sferlazza, S., Mariottini, A., Niccolini, M., Coppi, T., Miozzo, M., La Mantia, T., Maetzke, F.,
A Case Study of the Application of Hand-held Mobile Laser Scanning In The Planning of An Italian Forest (alpe Di Catenaia, Tuscany),
ISPRS21(B2-2021: 763-770).
DOI Link 2201

Mizoguchi, T., Ishii, A., Nakamura, H.,
Individual Tree Species Classification Based On Terrestrial Laser Scanning Using Curvature Estimation and Convolutional Neural Network,
DOI Link 1912

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Analysis, Canopy Heights, LiDAR .

Last update:Jul 13, 2024 at 15:27:21