24.4.13.7.8 Forest Analysis, Depth, LiDAR, Laser Scanner

Chapter Contents (Back)
Forest. LIDAR. Terrestrial LiDAR:
See also Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS.
See also Canopy Height Measurement.
See also Forest Analysis, IFSAR, SAR, Radar.
See also Mangrove Analysis, Swamps, Coasts, Trees.

Lucas, R.M., Lee, A.C., Williams, M.L.,
Enhanced Simulation of Radar Backscatter From Forests Using LiDAR and Optical Data,
GeoRS(44), No. 10, October 2006, pp. 2736-2754.
IEEE DOI 0609
BibRef

Chasmer, L.[Laura], Hopkinson, C.[Chris], Smith, B.[Brent], Treitz, P.[Paul],
Examining the Influence of Changing Laser Pulse Repetition Frequencies on Conifer Forest Canopy Returns,
PhEngRS(72), No. 12, December 2006, pp. 1359-1368.
WWW Link. 0704
The characteristics associated with differing laser pulse emission frequencies are found to vary the penetration of pulses within conifer forest canopies. BibRef

Hinsley, S.A.[Shelley A.], Hill, R.A.[Ross A.], Bellamy, P.E., Balzter, H.[Heiko],
The Application of Lidar in Woodland Bird Ecology: Climate, Canopy Structure, and Habitat Quality,
PhEngRS(72), No. 12, December 2006, pp. 1399-1406.
WWW Link. 0704
Measuring woodland vegetation structure and the relationship of climate in determining habitat quality for breeding birds. BibRef

Hill, R.A.[Ross A.], Hinsley, S.A.[Shelley A.],
Airborne Lidar for Woodland Habitat Quality Monitoring: Exploring the Significance of Lidar Data Characteristics when Modelling Organism-Habitat Relationships,
RS(7), No. 4, 2015, pp. 3446-3466.
DOI Link 1505
BibRef

Evans, J.S.[Jeffrey S.], Hudak, A.T.[Andrew T.],
A Multiscale Curvature Algorithm for Classifying Discrete Return LiDAR in Forested Environments,
GeoRS(45), No. 4, April 2007, pp. 1029-1038.
IEEE DOI 0704
BibRef

Hudak, A.T., Evans, J.S., Stuart Smith, A.,
LiDAR Utility for Natural Resource Managers,
RS(1), No. 4, December 2009, pp. 934-951.
DOI Link 1203
BibRef

Dalponte, M., Bruzzone, L.[Lorenzo], Gianelle, D.,
Fusion of Hyperspectral and LIDAR Remote Sensing Data for Classification of Complex Forest Areas,
GeoRS(46), No. 5, May 2008, pp. 1416-1427.
IEEE DOI 0804

See also System for the Estimation of Single-Tree Stem Diameter and Volume Using Multireturn LIDAR Data, A. BibRef

Wang, C., Menenti, M., Stoll, M.P., Feola, A., Belluco, E., Marani, M.,
Separation of Ground and Low Vegetation Signatures in LiDAR Measurements of Salt-Marsh Environments,
GeoRS(47), No. 7, July 2009, pp. 2014-2023.
IEEE DOI 0906
BibRef

Disney, M.I., Lewis, P.E., Bouvet, M., Prieto-Blanco, A., Hancock, S.,
Quantifying Surface Reflectivity for Spaceborne Lidar via Two Independent Methods,
GeoRS(47), No. 9, September 2009, pp. 3262-3271.
IEEE DOI 0909
BibRef

Hancock, S.[Steven], Disney, M.I.[Mathias I.], Lewis, P.E.[Philip E.], Muller, J.P.[Jan-Peter],
Exploring the Measurement Of Forests With Full Waveform LIDAR through Monte-Carlo Ray Tracing,
ISPRS08(B1: 235 ff).
PDF File. 0807
BibRef

Korpela, I.[Ilkka], Orka, H.O.[Hans Ole], Hyyppa, J.[Juha], Heikkinen, V.[Ville], Tokola, T.[Timo],
Range and AGC normalization in airborne discrete-return LiDAR intensity data for forest canopies,
PandRS(65), No. 4, July 2010, pp. 369-379.
Elsevier DOI 1003
Vegetation; Forestry; Radiometry; Laser scanning; Classification BibRef

Krooks, A., Krooks, A.[Anssi], Hyyppä, J.[Juha], Lyytikäinen-Saarenmaa, P.[Päivi], Jaakkola, A.[Anttoni], Kaasalainen, S.[Sanna],
Using Stationary And Mobile Laser Scanner To Detect Forest Defoliation,
CloseRange10(xx-yy).
PDF File. 1006
BibRef

Ahokas, E., Hyyppä, J., Yu, X.W.[Xiao-Wei], Holopainen, M.,
Transmittance of Airborne Laser Scanning Pulses for Boreal Forest Elevation Modeling,
RS(3), No. 7, July 2011, pp. 1365-1379.
DOI Link 1203
BibRef

Hyyppä, J., Holopainen, M., Olsson, H.,
Laser Scanning in Forests,
RS(4), No. 10, October 2012, pp. 2919-2922.
DOI Link 1210
BibRef

Yu, X.W.[Xiao-Wei], Hyyppä, H., Kaartinen, H., Hyyppä, J., Ahokas, E., Kaasalainen, S.,
Applicability of first pulse derived digital terrain models for boreal forest zone,
Laser05(xx-yy).
PDF File. 0509
BibRef

Vehmas, M., Eerikäinen, K., Peuhkurinen, J., Packalén, P., Maltamo, M.,
Airborne Laser Scanning for the Site Type Identification of Mature Boreal Forest Stands,
RS(3), No. 1, January 2011, pp. 100-116.
DOI Link 1203
BibRef

Bater, C.W., Wulder, M.A., Coops, N.C., Nelson, R.F., Hilker, T., Naesset, E.,
Stability of Sample-Based Scanning-LiDAR-Derived Vegetation Metrics for Forest Monitoring,
GeoRS(49), No. 6, June 2011, pp. 2385-2392.
IEEE DOI 1106
BibRef

Goodwin, N.R., Coops, N.C., Bater, C.W., Gergel, S.E.,
Assessment of Sub-Canopy Structure in a Complex Coniferous Forest,
Laser07(169).
PDF File. 0709
BibRef

Bater, C.W., Coops, N.C., Gergel, S.E., Goodwin, N.R.,
Towards the Estimation of Tree Structural Class in Northwest Coastal Forests Using Lidar Remote Sensing,
Laser07(38).
PDF File. 0709
BibRef

Liu, P.W.[Pang-Wei], Lee, H.[Heezin], Judge, J.[Jasmeet], Wright, W.C.[William C.], Slatton, K.C.[K. Clint],
Prediction of L-band signal attenuation in forests using 3D vegetation structure from airborne LiDAR,
PandRS(66), No. 5, September 2011, pp. 642-651.
Elsevier DOI 1110
Airborne LiDAR; Microwave attenuation; Remote sensing; GPS; 3D vegetation structure BibRef

Wallace, A.M., Nichol, C.J., Woodhouse, I.,
Recovery of Forest Canopy Parameters by Inversion of Multispectral LiDAR Data,
RS(4), No. 2, February 2012, pp. 509-531.
DOI Link 1203
BibRef

Tuominen, S., Haapanen, R.,
Comparison of Grid-Based and Segment-Based Estimation of Forest Attributes Using Airborne Laser Scanning and Digital Aerial Imagery,
RS(3), No. 5, May 2011, pp. 945-961.
DOI Link 1203
BibRef

Eysn, L., Hollaus, M., Schadauer, K., Pfeifer, N.,
Forest Delineation Based on Airborne LIDAR Data,
RS(4), No. 3, March 2012, pp. 2012, 43, 762-783;.
DOI Link 1204
BibRef

Wallace, L., Lucieer, A., Watson, C., Turner, D.,
Development of a UAV-LiDAR System with Application to Forest Inventory,
RS(4), No. 6, June 2012, pp. 1519-1543.
DOI Link 1208
BibRef

Fricker, G., Saatchi, S., Meyer, V., Gillespie, T., Sheng, Y.,
Application of Semi-Automated Filter to Improve Waveform Lidar Sub-Canopy Elevation Model,
RS(4), No. 6, June 2012, pp. 1494-1518.
DOI Link 1208
BibRef

Leutner, B., Reineking, B., Müller, J., Bachmann, M., Beierkuhnlein, C.[Carl], Dech, S., Wegmann, M.,
Modelling Forest alpha-Diversity and Floristic Composition: On the Added Value of LiDAR plus Hyperspectral Remote Sensing,
RS(4), No. 9, September 2012, pp. 2818-2845.
DOI Link 1210
BibRef

Defibaugh y Chávez, J., Tullis, J.,
Deciduous Forest Structure Estimated with LIDAR-Optimized Spectral Remote Sensing,
RS(5), No. 1, January 2013, pp. 155-182.
DOI Link 1302
BibRef

Hellesen, T., Matikainen, L.,
An Object-Based Approach for Mapping Shrub and Tree Cover on Grassland Habitats by Use of LiDAR and CIR Orthoimages,
RS(5), No. 2, February 2013, pp. 558-583.
DOI Link 1303
BibRef

Bremer, M., Rutzinger, M., Wichmann, V.,
Derivation of tree skeletons and error assessment using LiDAR point cloud data of varying quality,
PandRS(80), No. 1, June 2013, pp. 39-50.
Elsevier DOI 1305
Laser scanning; Branch extraction; Skeletonization; Eigenvectors; Data reduction; Object-based point cloud analysis BibRef

Whitehurst, A., Swatantran, A., Blair, J.B., Hofton, M., Dubayah, R.,
Characterization of Canopy Layering in Forested Ecosystems Using Full Waveform Lidar,
RS(5), No. 4, April 2013, pp. 2014-2036.
DOI Link 1305
BibRef

Leiterer, R.[Reik], Mücke, W.[Werner], Hollaus, M.[Markus], Pfeifer, N.[Norbert], Schaepman, M.E.[Michael E.],
Operational forest structure monitoring using airborne laser scanning,
PFG(2013), No. 3, 2013, pp. 173-184.
DOI Link 1306
BibRef

Hosoi, F.[Fumiki], Nakai, Y.[Yohei], Omasa, K.[Kenji],
3-D voxel-based solid modeling of a broad-leaved tree for accurate volume estimation using portable scanning lidar,
PandRS(82), No. 1, August 2013, pp. 41-48.
Elsevier DOI 1306
Portable ground-based scanning lidar; Solid model; Voxel; Woody material volume BibRef

Korpela, I.[Ilkka], Hovi, A.[Aarne], Korhonen, L.[Lauri],
Backscattering of Individual LIDAR Pulses from Forest Canopies Explained by Photogrammetrically Derived Vegetation Structure,
PandRS(83), No. 1, 2013, pp. 81-93.
Elsevier DOI 1307
BibRef
Earlier: Hannover13(171-176).
DOI Link 1308
Close-range photogrammetry BibRef

Hovi, A., Korpela, I.,
Real and Simulated Waveform Recording LIDAR Data in Boreal Juvenile Forest Vegetation,
Hannover13(145-150).
DOI Link 1308
BibRef

Nurminen, K.[Kimmo], Karjalainen, M.[Mika], Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Honkavaara, E.[Eija],
Performance of dense digital surface models based on image matching in the estimation of plot-level forest variables,
PandRS(83), No. 1, 2013, pp. 104-115.
Elsevier DOI 1308
Image matching BibRef

Maguya, A.S.[Almasi S.], Junttila, V.[Virpi], Kauranne, T.[Tuomo],
Adaptive algorithm for large scale DTM interpolation from lidar data for forestry applications in steep forested terrain,
PandRS(85), No. 1, 2013, pp. 74-83.
Elsevier DOI 1310
LiDAR processing BibRef

Pope, G.[Graham], Treitz, P.[Paul],
Leaf Area Index (LAI) Estimation in Boreal Mixedwood Forest of Ontario, Canada Using Light Detection and Ranging (LiDAR) and WorldView-2 Imagery,
RS(5), No. 10, 2013, pp. 5040-5063.
DOI Link 1311
BibRef

Wang, Q.A.[Qi-Ang], Pang, Y.[Yong], Li, Z.Y.[Zeng-Yuan], Chen, E.[Erxue], Sun, G.Q.[Guo-Qing], Tan, B.X.[Bing-Xiang],
Improvement and Application of the Conifer Forest Multiangular Hybrid GORT Model MGeoSAIL,
GeoRS(51), No. 10, 2013, pp. 5047-5059.
IEEE DOI 1311
radiative transfer BibRef

Ediriweera, S.[Sisira], Pathirana, S.[Sumith], Danaher, T.[Tim], Nichols, D.[Doland], Moffiet, T.[Trevor],
Evaluation of Different Topographic Corrections for Landsat TM Data by Prediction of Foliage Projective Cover (FPC) in Topographically Complex Landscapes,
RS(5), No. 12, 2013, pp. 6767-6789.
DOI Link 1402
BibRef
Earlier:
Impact Of Different Topographic Corrections On Prediction Accuracy Of Foliage Projective Cover (FPC) in a Topographically Complex Terrain,
AnnalsPRS(I-7), No. 2012, pp. 123-128.
DOI Link 1209
BibRef

Wallace, A.M., McCarthy, A., Nichol, C.J., Ren, X., Morak, S., Martinez-Ramirez, D., Woodhouse, I.H., Buller, G.S.,
Design and Evaluation of Multispectral LiDAR for the Recovery of Arboreal Parameters,
GeoRS(52), No. 8, August 2014, pp. 4942-4954.
IEEE DOI 1403
Instruments BibRef

Torabzadeh, H.[Hossein], Morsdorf, F.[Felix], Schaepman, M.E.[Michael E.],
Fusion of imaging spectroscopy and airborne laser scanning data for characterization of forest ecosystems: A review,
PandRS(97), No. 1, 2014, pp. 25-35.
Elsevier DOI 1410
Forest ecosystems BibRef

Räsänen, A.[Aleksi], Kuitunen, M.[Markku], Tomppo, E.[Erkki], Lensu, A.[Anssi],
Coupling high-resolution satellite imagery with ALS-based canopy height model and digital elevation model in object-based boreal forest habitat type classification,
PandRS(94), No. 1, 2014, pp. 169-182.
Elsevier DOI 1407
Habitat type mapping BibRef

Valbuena, R.[Rubén], Vauhkonen, J.[Jari], Packalen, P.[Petteri], Pitkänen, J.H.[Ju-Ho], Maltamo, M.[Matti],
Comparison of airborne laser scanning methods for estimating forest structure indicators based on Lorenz curves,
PandRS(95), No. 1, 2014, pp. 23-33.
Elsevier DOI 1408
Forest structure BibRef

Parent, J.R.[Jason R.], Volin, J.C.[John C.],
Assessing the potential for leaf-off LiDAR data to model canopy closure in temperate deciduous forests,
PandRS(95), No. 1, 2014, pp. 134-145.
Elsevier DOI 1408
LiDAR BibRef

Vauhkonen, J.[Jari], Næsset, E.[Erik], Gobakken, T.[Terje],
Deriving airborne laser scanning based computational canopy volume for forest biomass and allometry studies,
PandRS(96), No. 1, 2014, pp. 57-66.
Elsevier DOI 1410
Light Detection and Ranging (LiDAR) BibRef

Ene, L., Naesset, E., Gobakken, T.,
Simulating Sampling Efficiency in Airborne Laser Scanning Based Forest Inventory,
Laser07(114).
PDF File. 0709
BibRef

Wallace, L.O., Lucieer, A., Watson, C.S.,
Evaluating Tree Detection and Segmentation Routines on Very High Resolution UAV LiDAR Data,
GeoRS(52), No. 12, December 2014, pp. 7619-7628.
IEEE DOI 1410
BibRef
Earlier:
Assessing the Feasibility of UAV-Based LIDAR for High Resolution Forest Change Detection,
ISPRS12(XXXIX-B7:499-504).
DOI Link 1209
BibRef

Paris, C., Bruzzone, L.,
A Three-Dimensional Model-Based Approach to the Estimation of the Tree Top Height by Fusing Low-Density LiDAR Data and Very High Resolution Optical Images,
GeoRS(53), No. 1, January 2015, pp. 467-480.
IEEE DOI 1410
geophysical techniques BibRef

Peng, S.Z.[Shou-Zhang], Zhao, C.Y.[Chuan-Yan], Xu, Z.L.[Zhong-Lin],
Modeling spatiotemporal patterns of understory light intensity using airborne laser scanner (LiDAR),
PandRS(97), No. 1, 2014, pp. 195-203.
Elsevier DOI 1410
LiDAR BibRef

Peterson, B.[Birgit], Nelson, K.J.[Kurtis J.],
Mapping Forest Height in Alaska Using GLAS, Landsat Composites, and Airborne LiDAR,
RS(6), No. 12, 2014, pp. 12409-12426.
DOI Link 1412
BibRef

Fayad, I.[Ibrahim], Baghdadi, N.[Nicolas], Bailly, J.S.[Jean-Stéphane], Barbier, N.[Nicolas], Gond, V.[Valéry], Hérault, B.[Bruno], El Hajj, M.[Mahmoud], Fabre, F.[Frédéric], Perrin, J.[José],
Regional Scale Rain-Forest Height Mapping Using Regression-Kriging of Spaceborne and Airborne LiDAR Data: Application on French Guiana,
RS(8), No. 3, 2016, pp. 240.
DOI Link 1604
BibRef

Ryding, J.[Joseph], Williams, E.[Emily], Smith, M.J.[Martin J.], Eichhorn, M.P.[Markus P.],
Assessing Handheld Mobile Laser Scanners for Forest Surveys,
RS(7), No. 1, 2015, pp. 1095-1111.
DOI Link 1502
BibRef

Ma, H.[Han], Song, J.L.[Jin-Ling], Wang, J.D.[Jin-Di],
Forest Canopy LAI and Vertical FAVD Profile Inversion from Airborne Full-Waveform LiDAR Data Based on a Radiative Transfer Model,
RS(7), No. 2, 2015, pp. 1897-1914.
DOI Link 1503
BibRef

Parent, J.R.[Jason R.], Volin, J.C.[John C.], Civco, D.L.[Daniel L.],
A fully-automated approach to land cover mapping with airborne LiDAR and high resolution multispectral imagery in a forested suburban landscape,
PandRS(104), No. 1, 2015, pp. 18-29.
Elsevier DOI 1505
Land cover BibRef

Lindberg, E.[Eva], Roberge, J.M.[Jean-Michel], Johansson, T.[Therese], Hjältén, J.[Joakim],
Can Airborne Laser Scanning (ALS) and Forest Estimates Derived from Satellite Images Be Used to Predict Abundance and Species Richness of Birds and Beetles in Boreal Forest?,
RS(7), No. 4, 2015, pp. 4233-4252.
DOI Link 1505
BibRef

Shang, X.X.[Xiao-Xia], Chazette, P.[Patrick],
End-to-End Simulation for a Forest-Dedicated Full-Waveform Lidar Onboard a Satellite Initialized from Airborne Ultraviolet Lidar Experiments,
RS(7), No. 5, 2015, pp. 5222-5255.
DOI Link 1506
BibRef

Montealegre, A.L.[Antonio Luis], Lamelas, M.T.[María Teresa], de la Riva, J.[Juan],
Interpolation Routines Assessment in ALS-Derived Digital Elevation Models for Forestry Applications,
RS(7), No. 7, 2015, pp. 8631.
DOI Link 1506
BibRef

Gökkaya, K.[Kemal], Thomas, V.A.[Valerie A.], Noland, T.L.[Thomas L.], McCaughey, H.[Harry], Morrison, I.[Ian], Treitz, P.[Paul],
Prediction of Macronutrients at the Canopy Level Using Spaceborne Imaging Spectroscopy and LiDAR Data in a Mixedwood Boreal Forest,
RS(7), No. 7, 2015, pp. 9045.
DOI Link 1506
BibRef

Junttila, V., Kauranne, T., Finley, A.O., Bradford, J.B.,
Linear Models for Airborne-Laser-Scanning-Based Operational Forest Inventory With Small Field Sample Size and Highly Correlated LiDAR Data,
GeoRS(53), No. 10, October 2015, pp. 5600-5612.
IEEE DOI 1509
remote sensing by laser beam BibRef

Yang, H.Q.[Hai-Quan], Chen, W.L.[Wen-Long], Qian, T.[Tianlu], Shen, D.[Dingtao], Wang, J.C.[Jie-Chen],
The Extraction of Vegetation Points from LiDAR Using 3D Fractal Dimension Analyses,
RS(7), No. 8, 2015, pp. 10815.
DOI Link 1509
BibRef

Junttila, S.[Samuli], Kaasalainen, S.[Sanna], Vastaranta, M.[Mikko], Hakala, T.[Teemu], Nevalainen, O.[Olli], Holopainen, M.[Markus],
Investigating Bi-Temporal Hyperspectral Lidar Measurements from Declined Trees: Experiences from Laboratory Test,
RS(7), No. 10, 2015, pp. 13863.
DOI Link 1511
BibRef

Bonnet, S.[Stéphanie], Gaulton, R.[Rachel], Lehaire, F.[François], Lejeune, P.[Philippe],
Canopy Gap Mapping from Airborne Laser Scanning: An Assessment of the Positional and Geometrical Accuracy,
RS(7), No. 9, 2015, pp. 11267.
DOI Link 1511
BibRef

Dupuis, J.[Jan], Paulus, S.[Stefan], Mahlein, A.K.[Anne-Katrin], Kuhlmann, Eichert, T.[Thomas],
The Impact of different Leaf Surface Tissues on active 3D Laser Triangulation Measurements,
PFG(2015), No. 6, 2015, pp. 437-447.
DOI Link 1601
BibRef

Zhao, X.Q.[Xiao-Qian], Guo, Q.H.[Qing-Hua], Su, Y.J.[Yan-Jun], Xue, B.L.[Bao-Lin],
Improved progressive TIN densification filtering algorithm for airborne LiDAR data in forested areas,
PandRS(117), No. 1, 2016, pp. 79-91.
Elsevier DOI 1605
Light detection and ranging BibRef

Niemi, M.T.[Mikko T.], Vauhkonen, J.[Jari],
Extracting Canopy Surface Texture from Airborne Laser Scanning Data for the Supervised and Unsupervised Prediction of Area-Based Forest Characteristics,
RS(8), No. 7, 2016, pp. 582.
DOI Link 1608
BibRef

Oshio, H., Asawa, T.,
Estimating the Solar Transmittance of Urban Trees Using Airborne LiDAR and Radiative Transfer Simulation,
GeoRS(54), No. 9, September 2016, pp. 5483-5492.
IEEE DOI 1609
airborne radar BibRef

You, H.T.[Hao-Tian], Wang, T.J.[Tie-Jun], Skidmore, A.K.[Andrew K.], Xing, Y.Q.[Yan-Qiu],
Quantifying the Effects of Normalisation of Airborne LiDAR Intensity on Coniferous Forest Leaf Area Index Estimations,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Dechesne, C.[Clément], Mallet, C.[Clément], Le Bris, A.[Arnaud], Gouet-Brunet, V.[Valérie],
Semantic segmentation of forest stands of pure species combining airborne lidar data and very high resolution multispectral imagery,
PandRS(126), No. 1, 2017, pp. 129-145.
Elsevier DOI 1704
Lidar BibRef

Dechesne, C.[Clément], Mallet, C.[Clément], Le Bris, A.[Arnaud], Gouet, V.[Valérie], Hervieu, A.[Alexandre],
Forest Stand Segmentation Using Airborne Lidar Data And Very High Resolution Multispectral Imagery,
ISPRS16(B3: 207-214).
DOI Link 1610
BibRef

Awaya, Y.[Yoshio], Takahashi, T.[Tomoaki],
Evaluating the Differences in Modeling Biophysical Attributes between Deciduous Broadleaved and Evergreen Conifer Forests Using Low-Density Small-Footprint LiDAR Data,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Jaakkola, A.[Anttoni], Hyyppä, J.[Juha], Yu, X.W.[Xiao-Wei], Kukko, A.[Antero], Kaartinen, H.[Harri], Liang, X.L.[Xin-Lian], Hyyppä, H.[Hannu], Wang, Y.S.[Yun-Sheng],
Autonomous Collection of Forest Field Reference: The Outlook and a First Step with UAV Laser Scanning,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Hyyppä, E.[Eric], Hyyppä, J.[Juha], Hakala, T.[Teemu], Kukko, A.[Antero], Wulder, M.A.[Michael A.], White, J.C.[Joanne C.], Pyörälä, J.[Jiri], Yu, X.W.[Xiao-Wei], Wang, Y.S.[Yun-Sheng], Virtanen, J.P.[Juho-Pekka], Pohjavirta, O.[Onni], Liang, X.[Xinlian], Holopainen, M.[Markus], Kaartinen, H.[Harri],
Under-canopy UAV laser scanning for accurate forest field measurements,
PandRS(164), 2020, pp. 41-60.
Elsevier DOI 2005
Airborne laser scanning, UAV, Under-canopy flight, Stem volume, Stem curve, SLAM BibRef

Muhojoki, J.[Jesse], Tavi, D.[Daniella], Hyyppä, E.[Eric], Lehtomäki, M.[Matti], Faitli, T.[Tamás], Kaartinen, H.[Harri], Kukko, A.[Antero], Hakala, T.[Teemu], Hyyppä, J.[Juha],
Benchmarking Under- and Above-Canopy Laser Scanning Solutions for Deriving Stem Curve and Volume in Easy and Difficult Boreal Forest Conditions,
RS(16), No. 10, 2024, pp. 1721.
DOI Link 2405
BibRef

Hyyppä, E.[Eric], Yu, X.W.[Xiao-Wei], Kaartinen, H.[Harri], Hakala, T.[Teemu], Kukko, A.[Antero], Vastaranta, M.[Mikko], Hyyppä, J.[Juha],
Comparison of Backpack, Handheld, Under-Canopy UAV, and Above-Canopy UAV Laser Scanning for Field Reference Data Collection in Boreal Forests,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
BibRef

Piiroinen, R.[Rami], Heiskanen, J.[Janne], Maeda, E.[Eduardo], Viinikka, A.[Arto], Pellikka, P.[Petri],
Classification of Tree Species in a Diverse African Agroforestry Landscape Using Imaging Spectroscopy and Laser Scanning,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Shi, Y.F.[Yi-Fang], Wang, T.J.[Tie-Jun], Skidmore, A.K.[Andrew K.], Heurich, M.[Marco],
Important LiDAR metrics for discriminating forest tree species in Central Europe,
PandRS(137), 2018, pp. 163-174.
Elsevier DOI 1802
Tree species, Natural forest, Airborne LiDAR, Morphology, Leaf-on, Leaf-off BibRef

Persson, H.J.[Henrik J.], Olsson, H.[Håkan], Soja, M.J.[Maciej J.], Ulander, L.M.H.[Lars M.H.], Fransson, J.E.S.[Johan E.S.],
Experiences from Large-Scale Forest Mapping of Sweden Using TanDEM-X Data,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Liu, J.[Jing], Skidmore, A.K.[Andrew K.], Jones, S.[Simon], Wang, T.J.[Tie-Jun], Heurich, M.[Marco], Zhu, X.[Xi], Shi, Y.F.[Yi-Fang],
Large off-nadir scan angle of airborne LiDAR can severely affect the estimates of forest structure metrics,
PandRS(136), 2018, pp. 13-25.
Elsevier DOI 1802
Gap fraction, Vertical gap fraction profile, Off-nadir scan angle, Airborne LiDAR BibRef

Fedrigo, M.[Melissa], Newnham, G.J.[Glenn J.], Coops, N.C.[Nicholas C.], Culvenor, D.S.[Darius S.], Bolton, D.K.[Douglas K.], Nitschke, C.R.[Craig R.],
Predicting temperate forest stand types using only structural profiles from discrete return airborne lidar,
PandRS(136), 2018, pp. 106-119.
Elsevier DOI 1802
Lidar, Linear unmixing, Principal components, Random forest, Structure BibRef

Ayrey, E.[Elias], Hayes, D.J.[Daniel J.],
The Use of Three-Dimensional Convolutional Neural Networks to Interpret LiDAR for Forest Inventory,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
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Marinelli, D., Paris, C., Bruzzone, L.,
A Novel Approach to 3-D Change Detection in Multitemporal LiDAR Data Acquired in Forest Areas,
GeoRS(56), No. 6, June 2018, pp. 3030-3046.
IEEE DOI 1806
Data models, Distance measurement, Forestry, Laser radar, Remote sensing, Vegetation, remote sensing BibRef

Simonson, W.[William], Allen, H.[Harriet], Coomes, D.[David],
Effect of Tree Phenology on LiDAR Measurement of Mediterranean Forest Structure,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
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Liu, Y.[Yanan], Gong, W.S.[Wei-Shu], Hu, X.Y.[Xiang-Yun], Gong, J.Y.[Jian-Ya],
Forest Type Identification with Random Forest Using Sentinel-1A, Sentinel-2A, Multi-Temporal Landsat-8 and DEM Data,
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DOI Link 1806
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Pearse, G.D.[Grant D.], Dash, J.P.[Jonathan P.], Persson, H.J.[Henrik J.], Watt, M.S.[Michael S.],
Comparison of high-density LiDAR and satellite photogrammetry for forest inventory,
PandRS(142), 2018, pp. 257-267.
Elsevier DOI 1807
Forest inventory, Stereo, Satellite, Photogrammetry, LiDAR, Airborne laser scanning, Pléiades, Remote sensing, Radiata pine BibRef

Liang, X.[Xinlian], Kukko, A.[Antero], Hyyppä, J.[Juha], Lehtomäki, M.[Matti], Pyörälä, J.[Jiri], Yu, X.W.[Xiao-Wei], Kaartinen, H.[Harri], Jaakkola, A.[Anttoni], Wang, Y.S.[Yun-Sheng],
In-situ measurements from mobile platforms: An emerging approach to address the old challenges associated with forest inventories,
PandRS(143), 2018, pp. 97-107.
Elsevier DOI 1808
In-situ, Terrestrial point cloud, Mobile, Wearable, Mobile laser scanning, Personal laser scanning, Forest inventories BibRef

Palma, M.[Marco], Casado, M.R.[Monica Rivas], Pantaleo, U.[Ubaldo], Pavoni, G.[Gaia], Pica, D.[Daniela], Cerrano, C.[Carlo],
SfM-Based Method to Assess Gorgonian Forests (Paramuricea clavata (Cnidaria, Octocorallia)),
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
Key structuring species of the Mediterranean region. BibRef

Urbazaev, M.[Mikhail], Cremer, F.[Felix], Migliavacca, M.[Mirco], Reichstein, M.[Markus], Schmullius, C.[Christiane], Thiel, C.[Christian],
Potential of Multi-Temporal ALOS-2 PALSAR-2 ScanSAR Data for Vegetation Height Estimation in Tropical Forests of Mexico,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809
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Liu, J.C.[Jin-Cheng], Feng, Z.K.[Zhong-Ke], Yang, L.Y.[Li-Yan], Mannan, A.[Abdul], Khan, T.U.[Tauheed Ullah], Zhao, Z.Y.[Zi-Yu], Cheng, Z.[Zhuxin],
Extraction of Sample Plot Parameters from 3D Point Cloud Reconstruction Based on Combined RTK and CCD Continuous Photography,
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DOI Link 1809
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Wästlund, A.[André], Holmgren, J.[Johan], Lindberg, E.[Eva], Olsson, H.[Håkan],
Forest Variable Estimation Using a High Altitude Single Photon Lidar System,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
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Fankhauser, K.E.[Kathryn E.], Strigul, N.S.[Nikolay S.], Gatziolis, D.[Demetrios],
Augmentation of Traditional Forest Inventory and Airborne Laser Scanning with Unmanned Aerial Systems and Photogrammetry for Forest Monitoring,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
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Mahlangu, P.[Precious], Mathieu, R.[Renaud], Wessels, K.[Konrad], Naidoo, L.[Laven], Verstraete, M.[Michel], Asner, G.[Gregory], Main, R.[Russell],
Indirect Estimation of Structural Parameters in South African Forests Using MISR-HR and LiDAR Remote Sensing Data,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
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Piermattei, L.[Livia], Marty, M.[Mauro], Karel, W.[Wilfried], Ressl, C.[Camillo], Hollaus, M.[Markus], Ginzler, C.[Christian], Pfeifer, N.[Norbert],
Impact of the Acquisition Geometry of Very High-Resolution Pléiades Imagery on the Accuracy of Canopy Height Models over Forested Alpine Regions,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
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Liu, K.[Kun], Shen, X.[Xin], Cao, L.[Lin], Wang, G.B.[Gui-Bin], Cao, F.L.[Fu-Liang],
Estimating forest structural attributes using UAV-LiDAR data in Ginkgo plantations,
PandRS(146), 2018, pp. 465-482.
Elsevier DOI 1812
LiDAR, UAV, Forest structural attributes, Ginkgo, Planted forest, Point cloud density BibRef

de Almeida, D.R.A.[Danilo Roberti Alves], Stark, S.C.[Scott C.], Shao, G.[Gang], Schietti, J.[Juliana], Nelson, B.W.[Bruce Walker], Silva, C.A.[Carlos Alberto], Gorgens, E.B.[Eric Bastos], Valbuena, R.[Ruben], de Almeida Papa, D.[Daniel], Santin Brancalion, P.H.[Pedro Henrique],
Optimizing the Remote Detection of Tropical Rainforest Structure with Airborne Lidar: Leaf Area Profile Sensitivity to Pulse Density and Spatial Sampling,
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DOI Link 1901
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Fedrigo, M.[Melissa], Stewart, S.B.[Stephen B.], Roxburgh, S.H.[Stephen H.], Kasel, S.[Sabine], Bennett, L.T.[Lauren T.], Vickers, H.[Helen], Nitschke, C.R.[Craig R.],
Predictive Ecosystem Mapping of South-Eastern Australian Temperate Forests Using Lidar-Derived Structural Profiles and Species Distribution Models,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link 1901
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Ahl, R.[Robert], Hogland, J.[John], Brown, S.[Steve],
A Comparison of Standard Modeling Techniques Using Digital Aerial Imagery with National Elevation Datasets and Airborne LiDAR to Predict Size and Density Forest Metrics in the Sapphire Mountains MT, USA,
IJGI(8), No. 1, 2019, pp. xx-yy.
DOI Link 1901
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Xie, Z.L.[Zhu-Li], Chen, Y.L.[Yao-Liang], Lu, D.S.[Deng-Sheng], Li, G.Y.[Gui-Ying], Chen, E.[Erxue],
Classification of Land Cover, Forest, and Tree Species Classes with ZiYuan-3 Multispectral and Stereo Data,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
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Bruggisser, M.[Moritz], Hollaus, M.[Markus], Wang, D.[Di], Pfeifer, N.[Norbert],
Adaptive Framework for the Delineation of Homogeneous Forest Areas Based on LiDAR Points,
RS(11), No. 2, 2019, pp. xx-yy.
DOI Link 1902
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Domingo, D.[Darío], Alonso, R.[Rafael], Lamelas, M.T.[María Teresa], Montealegre, A.L.[Antonio Luis], Rodríguez, F.[Francisco], de la Riva, J.[Juan],
Temporal Transferability of Pine Forest Attributes Modeling Using Low-Density Airborne Laser Scanning Data,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902
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Li, J.P.[Jian-Ping], Yang, B.S.[Bi-Sheng], Cong, Y.Z.[Yang-Zi], Cao, L.[Lin], Fu, X.Y.[Xiao-Yao], Dong, Z.[Zhen],
3D Forest Mapping Using A Low-Cost UAV Laser Scanning System: Investigation and Comparison,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
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Pereira, I.S.[Iokanam Sales], Mendonça do Nascimento, H.E.[Henrique E.], Vicari, M.B.[Matheus Boni], Disney, M.[Mathias], DeLucia, E.H.[Evan H.], Domingues, T.[Tomas], Kruijt, B.[Bart], Lapola, D.[David], Meir, P.[Patrick], Norby, R.J.[Richard J.], Ometto, J.P.H.B.[Jean P.H.B.], Quesada, C.A.[Carlos A.], Rammig, A.[Anja], Hofhansl, F.[Florian],
Performance of Laser-Based Electronic Devices for Structural Analysis of Amazonian Terra-Firme Forests,
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Potential of Modern Photogrammetry Versus Airborne Laser Scanning for Estimating Forest Variables in a Mountain Environment,
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Chen, B.[Bowei], Pang, Y.[Yong], Li, Z.Y.[Zeng-Yuan], North, P.[Peter], Rosette, J.[Jacqueline], Sun, G.Q.[Guo-Qing], Suárez, J.[Juan], Bye, I.[Iain], Lu, H.[Hao],
Potential of Forest Parameter Estimation Using Metrics from Photon Counting LiDAR Data in Howland Research Forest,
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Saukkola, A.[Atte], Melkas, T.[Timo], Riekki, K.[Kirsi], Sirparanta, S.[Sanna], Peuhkurinen, J.[Jussi], Holopainen, M.[Markus], Hyyppä, J.[Juha], Vastaranta, M.[Mikko],
Predicting Forest Inventory Attributes Using Airborne Laser Scanning, Aerial Imagery, and Harvester Data,
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Carrasco, L.[Luis], Giam, X.L.[Xing-Li], Papes, M.[Monica], Sheldon, K.S.[Kimberly S.],
Metrics of Lidar-Derived 3D Vegetation Structure Reveal Contrasting Effects of Horizontal and Vertical Forest Heterogeneity on Bird Species Richness,
RS(11), No. 7, 2019, pp. xx-yy.
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Ni-Meister, W.[Wenge], Albanese, A.[Anthony], Lingo, F.[Francesca],
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Estimation of Changes of Forest Structural Attributes at Three Different Spatial Aggregation Levels in Northern California using Multitemporal LiDAR,
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Terrestrial Structure from Motion Photogrammetry for Deriving Forest Inventory Data,
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Huang, J.P.[Jia-Peng], Xing, Y.Q.[Yan-Qiu], You, H.T.[Hao-Tian], Qin, L.[Lei], Tian, J.[Jing], Ma, J.M.[Jian-Ming],
Particle Swarm Optimization-Based Noise Filtering Algorithm for Photon Cloud Data in Forest Area,
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Gaussian Process Regression for Forest Attribute Estimation From Airborne Laser Scanning Data,
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IEEE DOI 1906
Vegetation, Forestry, Ground penetrating radar, Uncertainty, Measurement, Estimation, Kernel, Area-based approach (ABA), machine learning BibRef

Kukkonen, M., Maltamo, M., Korhonen, L., Packalen, P.,
Multispectral Airborne LiDAR Data in the Prediction of Boreal Tree Species Composition,
GeoRS(57), No. 6, June 2019, pp. 3462-3471.
IEEE DOI 1906
Vegetation, Laser radar, Forestry, Instruments, Backscatter, Measurement, Remote sensing, Intensity correction, tree species classification BibRef

Choi, H.[Heejoon], Song, Y.[Youngkeun], Jang, Y.[Youngwoon],
Urban Forest Growth and Gap Dynamics Detected by Yearly Repeated Airborne Light Detection and Ranging (LiDAR): A Case Study of Cheonan, South Korea,
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Brieger, F.[Frederic], Herzschuh, U.[Ulrike], Pestryakova, L.A.[Luidmila A.], Bookhagen, B.[Bodo], Zakharov, E.S.[Evgenii S.], Kruse, S.[Stefan],
Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds,
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Sackov, I.[Ivan], Kulla, L.[Ladislav], Bucha, T.[Tomáš],
A Comparison of Two Tree Detection Methods for Estimation of Forest Stand and Ecological Variables from Airborne LiDAR Data in Central European Forests,
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Novo-Fernández, A.[Alís], Barrio-Anta, M.[Marcos], Recondo, C.[Carmen], Cámara-Obregón, A.[Asunción], López-Sánchez, C.A.[Carlos A.],
Integration of National Forest Inventory and Nationwide Airborne Laser Scanning Data to Improve Forest Yield Predictions in North-Western Spain,
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Dymond, J.R.[John R.], Zörner, J.[Jan], Shepherd, J.D.[James D.], Wiser, S.K.[Susan K.], Pairman, D.[David], Sabetizade, M.[Marmar],
Mapping Physiognomic Types of Indigenous Forest using Space-Borne SAR, Optical Imagery and Air-borne LiDAR,
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Dietmaier, A.[Annette], McDermid, G.J.[Gregory J.], Rahman, M.M.[Mir Mustafizur], Linke, J.[Julia], Ludwig, R.[Ralf],
Comparison of LiDAR and Digital Aerial Photogrammetry for Characterizing Canopy Openings in the Boreal Forest of Northern Alberta,
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DOI Link 1909
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Lehtola, V.V., Lehtomäki, M., Hyyti, H., Kaijaluoto, R., Kukko, A., Kaartinen, H., Hyyppä, J.,
Preregistration Classification of Mobile LIDAR Data Using Spatial Correlations,
GeoRS(57), No. 9, September 2019, pp. 6900-6915.
IEEE DOI 1909
Laser radar, Correlation, Simultaneous localization and mapping, Vegetation, Forestry, BibRef

Hillman, S.[Samuel], Wallace, L.[Luke], Reinke, K.[Karin], Hally, B.[Bryan], Jones, S.[Simon], Saldias, D.S.[Daisy S.],
A Method for Validating the Structural Completeness of Understory Vegetation Models Captured with 3D Remote Sensing,
RS(11), No. 18, 2019, pp. xx-yy.
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Wang, X.H.[Xiao-Hu], Zhang, Y.Z.[Yi-Zhuo], Xu, M.M.[Miao-Miao],
A Multi-Threshold Segmentation for Tree-Level Parameter Extraction in a Deciduous Forest Using Small-Footprint Airborne LiDAR Data,
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DOI Link 1909
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Balazy, R.[Radomir], Kaminska, A.[Agnieszka], Ciesielski, M.[Mariusz], Socha, J.[Jaroslaw], Pierzchalski, M.[Marcin],
Modeling the Effect of Environmental and Topographic Variables Affecting the Height Increment of Norway Spruce Stands in Mountainous Conditions with the Use of LiDAR Data,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910
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Pascual, A.[Adrián],
Using Tree Detection Based on Airborne Laser Scanning to Improve Forest Inventory Considering Edge Effects and the Co-Registration Factor,
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DOI Link 1911
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Zeng, K.[Kuo], Zheng, G.[Guang], Ma, L.X.[Li-Xia], Ju, W.M.[Wei-Min], Pang, Y.[Yong],
Modelling Three-Dimensional Spatiotemporal Distributions of Forest Photosynthetically Active Radiation Using UAV-Based Lidar Data,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
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Crespo-Peremarch, P.[Pablo], Ruiz, L.A.[Luis A.],
A Full-Waveform Airborne Laser Scanning Metric Extraction Tool for Forest Structure Modelling. Do Scan Angle and Radiometric Correction Matter?,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001
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Roberts, O.[Osian], Bunting, P.[Pete], Hardy, A.[Andy], McInerney, D.[Daniel],
Sensitivity Analysis of the DART Model for Forest Mensuration with Airborne Laser Scanning,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001
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Pascual, A.[Adrián], Guerra-Hernández, J.[Juan], Cosenza, D.N.[Diogo N.], Sandoval, V.[Vicente],
The Role of Improved Ground Positioning and Forest Structural Complexity When Performing Forest Inventory Using Airborne Laser Scanning,
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de Moura, Y.M.[Yhasmin Mendes], Balzter, H.[Heiko], Galvão, L.S.[Lênio S.], Dalagnol, R.[Ricardo], Espírito-Santo, F.[Fernando], Santos, E.G.[Erone G.], Garcia, M.[Mariano], Bispo, P.[Polyanna_da_Conceição], Oliveira, R.C.[Raimundo C.], Shimabukuro, Y.E.[Yosio E.],
Carbon Dynamics in a Human-Modified Tropical Forest: A Case Study Using Multi-Temporal LiDAR Data,
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DOI Link 2002
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Krzystek, P.[Peter], Serebryanyk, A.[Alla], Schnörr, C.[Claudius], Cervenka, J.[Jaroslav], Heurich, M.[Marco],
Large-Scale Mapping of Tree Species and Dead Trees in Šumava National Park and Bavarian Forest National Park Using Lidar and Multispectral Imagery,
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Guan, H.C.[Hong-Can], Su, Y.J.[Yan-Jun], Hu, T.Y.[Tian-Yu], Wang, R.[Rui], Ma, Q.[Qin], Yang, Q.L.[Qiu-Li], Sun, X.L.[Xi-Liang], Li, Y.M.[Yu-Mei], Jin, S.C.[Shi-Chao], Zhang, J.[Jing], Ma, Q.[Qin], Liu, M.[Min], Wu, F.Y.[Fa-Yun], Guo, Q.H.[Qing-Hua],
A Novel Framework to Automatically Fuse Multiplatform LiDAR Data in Forest Environments Based on Tree Locations,
GeoRS(58), No. 3, March 2020, pp. 2165-2177.
IEEE DOI 2003
Vegetation, Laser radar, Forestry, Tin, Unmanned aerial vehicles, Registers, Forest, tree location BibRef

Wang, X.F.[Xiao-Fei], Zheng, G.[Guang], Yun, Z.X.[Zeng-Xin], Moskal, L.M.[L. Monika],
Characterizing Tree Spatial Distribution Patterns Using Discrete Aerial Lidar Data,
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Wang, X.F.[Xiao-Fei], Zheng, G.[Guang], Yun, Z.X.[Zeng-Xin], Xu, Z.S.[Zhao-Shang], Moskal, L.M.[L. Monika], Tian, Q.J.[Qing-Jiu],
Characterizing the Spatial Variations of Forest Sunlit and Shaded Components Using Discrete Aerial Lidar,
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Cosenza, D.N.[Diogo N.], Pereira, L.G.[Luísa Gomes], Guerra-Hernández, J.[Juan], Pascual, A.[Adrián], Soares, P.[Paula], Tomé, M.[Margarida],
Impact of Calibrating Filtering Algorithms on the Quality of LiDAR-Derived DTM and on Forest Attribute Estimation through Area-Based Approach,
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DOI Link 2003
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Moran, C.J.[Christopher J.], Kane, V.R.[Van R.], Seielstad, C.A.[Carl A.],
Mapping Forest Canopy Fuels in the Western United States with LiDAR-Landsat Covariance,
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Itakura, K.[Kenta], Hosoi, F.[Fumiki],
Automatic Tree Detection from Three-Dimensional Images Reconstructed from 360° Spherical Camera Using YOLO v2,
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Fareed, N.[Nadeem], Rehman, K.[Khushbakht],
Integration of Remote Sensing and GIS to Extract Plantation Rows from A Drone-Based Image Point Cloud Digital Surface Model,
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DOI Link 2004
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Puliti, S.[Stefano], Breidenbach, J.[Johannes], Astrup, R.[Rasmus],
Estimation of Forest Growing Stock Volume with UAV Laser Scanning Data: Can It Be Done without Field Data?,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
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Krishna Moorthy, S.M., Calders, K., Vicari, M.B., Verbeeck, H.,
Improved Supervised Learning-Based Approach for Leaf and Wood Classification From LiDAR Point Clouds of Forests,
GeoRS(58), No. 5, May 2020, pp. 3057-3070.
IEEE DOI 2005
Forestry, Vegetation, Measurement by laser beam, Radiometry, Data models, tropical forests BibRef

Fan, G.P.[Guang-Peng], Nan, L.L.[Liang-Liang], Chen, F.X.[Fei-Xiang], Dong, Y.Q.[Yan-Qi], Wang, Z.M.[Zhi-Ming], Li, H.[Hao], Chen, D.Y.[Dan-Yu],
A New Quantitative Approach to Tree Attributes Estimation Based on LiDAR Point Clouds,
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Seidel, D.[Dominik], Annighöfer, P.[Peter], Ehbrecht, M.[Martin], Magdon, P.[Paul], Wöllauer, S.[Stephan], Ammer, C.[Christian],
Deriving Stand Structural Complexity from Airborne Laser Scanning Data: What Does It Tell Us about a Forest?,
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Meiforth, J.J.[Jane J.], Buddenbaum, H.[Henning], Hill, J.[Joachim], Shepherd, J.D.[James D.], Dymond, J.R.[John R.],
Stress Detection in New Zealand Kauri Canopies with WorldView-2 Satellite and LiDAR Data,
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Goodbody, T.R.H.[Tristan R.H.], Tompalski, P.[Piotr], Coops, N.C.[Nicholas C.], Hopkinson, C.[Chris], Treitz, P.[Paul], van Ewijk, K.[Karin],
Forest Inventory and Diversity Attribute Modelling Using Structural and Intensity Metrics from Multi-Spectral Airborne Laser Scanning Data,
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Matsuoka, M.[Masayuki], Moriya, H.[Hitoshi], Yoshioka, H.[Hiroki],
Correction of Canopy Shadow Effects on Reflectance in an Evergreen Conifer Forest Using a 3D Point Cloud,
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Damkjer, K.L., Foroosh, H.,
Lattice-Constrained Stratified Sampling for Point Cloud Levels of Detail,
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IEEE DOI 2007
Laser radar, Lattices, Measurement, Forestry, Spatial resolution, Estimation, stratified sampling BibRef

Sterenczak, K.[Krzysztof], Zaplata, R.[Rafal], Wójcik, J.[Jaroslaw], Kraszewski, B.[Bartlomiej], Mielcarek, M.[Milosz], Mitelsztedt, K.[Krzysztof], Bialczak, M.[Malgorzata], Krok, G.[Grzegorz], Kuberski, L.[Lukasz], Markiewicz, A.[Anna], Modzelewska, A.[Aneta], Parkitna, K.[Karolina], Piasecka, Z.[Zaneta], Pilch, K.[Kamil], Rzeczycki, K.[Karol], Sadkowski, R.[Rafal], Wietecha, M.[Martyna], Rysiak, P.[Piotr], von Gadow, K.[Klaus], Cieszewski, C.J.[Chris J.],
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Frank, B.[Bryce], Mauro, F.[Francisco], Temesgen, H.[Hailemariam],
Model-Based Estimation of Forest Inventory Attributes Using Lidar: A Comparison of the Area-Based and Semi-Individual Tree Crown Approaches,
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Moe, K.T.[Kyaw Thu], Owari, T.[Toshiaki], Furuya, N.[Naoyuki], Hiroshima, T.[Takuya], Morimoto, J.[Junko],
Application of UAV Photogrammetry with LiDAR Data to Facilitate the Estimation of Tree Locations and DBH Values for High-Value Timber Species in Northern Japanese Mixed-Wood Forests,
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Yu, X.W.[Xiao-Wei], Kukko, A.[Antero], Kaartinen, H.[Harri], Wang, Y.S.[Yun-Sheng], Liang, X.[Xinlian], Matikainen, L.[Leena], Hyyppä, J.[Juha],
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PandRS(168), 2020, pp. 268-276.
Elsevier DOI 2009
Forest, Single-photon, Multi-photon, Lidar, Airborne laser scanning BibRef

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Using Leaf-Off and Leaf-On Multispectral Airborne Laser Scanning Data to Characterize Seedling Stands,
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Yan, W.Y.[Wai Yeung], van Ewijk, K.[Karin], Treitz, P.[Paul], Shaker, A.[Ahmed],
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Multispectral LiDAR, LiDAR scan line correction, Overlap-driven intensity correction, Intensity banding, Random forests BibRef

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Prata, G.A.[Gabriel Atticciati], Broadbent, E.N.[Eben North], Alves de Almeida, D.R.[Danilo Roberti], St. Peter, J.[Joseph], Drake, J.[Jason], Medley, P.[Paul], Corte, A.P.D.[Ana Paula Dalla], Vogel, J.[Jason], Sharma, A.[Ajay], Silva, C.A.[Carlos Alberto], Zambrano, A.M.A.[Angelica Maria Almeyda], Valbuena, R.[Ruben], Wilkinson, B.[Ben],
Single-Pass UAV-Borne GatorEye LiDAR Sampling as a Rapid Assessment Method for Surveying Forest Structure,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
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Nevalainen, P.[Paavo], Li, Q.Q.[Qing-Qing], Melkas, T.[Timo], Riekki, K.[Kirsi], Westerlund, T.[Tomi], Heikkonen, J.[Jukka],
Navigation and Mapping in Forest Environment Using Sparse Point Clouds,
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DOI Link 2012
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Hartley, R.J.L.[Robin J. L.], Leonardo, E.M.[Ellen Mae], Massam, P.[Peter], Watt, M.S.[Michael S.], Estarija, H.J.[Honey Jane], Wright, L.[Liam], Melia, N.[Nathanael], Pearse, G.D.[Grant D.],
An Assessment of High-Density UAV Point Clouds for the Measurement of Young Forestry Trials,
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DOI Link 2012
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Araki, K.[Kazuho], Awaya, Y.[Yoshio],
Analysis and Prediction of Gap Dynamics in a Secondary Deciduous Broadleaf Forest of Central Japan Using Airborne Multi-LiDAR Observations,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101
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Rishmawi, K.[Khaldoun], Huang, C.Q.[Cheng-Quan], Zhan, X.[Xiwu],
Monitoring Key Forest Structure Attributes across the Conterminous United States by Integrating GEDI LiDAR Measurements and VIIRS Data,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
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Rishmawi, K.[Khaldoun], Huang, C.Q.[Cheng-Quan], Schleeweis, K.[Karen], Zhan, X.[Xiwu],
Integration of VIIRS Observations with GEDI-Lidar Measurements to Monitor Forest Structure Dynamics from 2013 to 2020 across the Conterminous United States,
RS(14), No. 10, 2022, pp. xx-yy.
DOI Link 2206
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Neuville, R.[Romain], Bates, J.S.[Jordan Steven], Jonard, F.[François],
Estimating Forest Structure from UAV-Mounted LiDAR Point Cloud Using Machine Learning,
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DOI Link 2102
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Brolly, G.[Gábor], Király, G.[Géza], Lehtomäki, M.[Matti], Liang, X.[Xinlian],
Voxel-Based Automatic Tree Detection and Parameter Retrieval from Terrestrial Laser Scans for Plot-Wise Forest Inventory,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103
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Tian, S.H.[Shi-Hao], Zheng, G.[Guang], Eitel, J.U.[Jan U.], Zhang, Q.[Qian],
A Lidar-Based 3-D Photosynthetically Active Radiation Model Reveals the Spatiotemporal Variations of Forest Sunlit and Shaded Leaves,
RS(13), No. 5, 2021, pp. xx-yy.
DOI Link 2103
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de Lima, R.S.[Raul Sampaio], Lang, M.[Mait], Burnside, N.G.[Niall G.], Peciña, M.V.[Miguel Villoslada], Arumäe, T.[Tauri], Laarmann, D.[Diana], Ward, R.D.[Raymond D.], Vain, A.[Ants], Sepp, K.[Kalev],
An Evaluation of the Effects of UAS Flight Parameters on Digital Aerial Photogrammetry Processing and Dense-Cloud Production Quality in a Scots Pine Forest,
RS(13), No. 6, 2021, pp. xx-yy.
DOI Link 2104
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Spracklen, B.[Ben], Spracklen, D.V.[Dominick V.],
Determination of Structural Characteristics of Old-Growth Forest in Ukraine Using Spaceborne LiDAR,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
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Palander, T.[Teijo], Kärhä, K.[Kalle],
Utilization of Image, LiDAR and Gamma-Ray Information to Improve Environmental Sustainability of Cut-to-Length Wood Harvesting Operations in Peatlands: A Management Systems Perspective,
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DOI Link 2106
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Martins-Neto, R.P.[Rorai Pereira], Tommaselli, A.M.G.[Antonio Maria Garcia], Imai, N.N.[Nilton Nobuhiro], David, H.C.[Hassan Camil], Miltiadou, M.[Milto], Honkavaara, E.[Eija],
Identification of Significative LiDAR Metrics and Comparison of Machine Learning Approaches for Estimating Stand and Diversity Variables in Heterogeneous Brazilian Atlantic Forest,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
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Vandendaele, B.[Bastien], Fournier, R.A.[Richard A.], Vepakomma, U.[Udayalakshmi], Pelletier, G.[Gaetan], Lejeune, P.[Philippe], Martin-Ducup, O.[Olivier],
Estimation of Northern Hardwood Forest Inventory Attributes Using UAV Laser Scanning (ULS): Transferability of Laser Scanning Methods and Comparison of Automated Approaches at the Tree- and Stand-Level,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
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Díaz-Varela, R.A.[Ramón Alberto], González-Ferreiro, E.[Eduardo],
3D Point Clouds in Forest Remote Sensing,
RS(13), No. 15, 2021, pp. xx-yy.
DOI Link 2108
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Park, S.H.[Sung-Hwan], Jung, H.S.[Hyung-Sup], Lee, S.[Sunmin], Kim, E.S.[Eun-Sook],
Mapping Forest Vertical Structure in Sogwang-ri Forest from Full-Waveform Lidar Point Clouds Using Deep Neural Network,
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Sun, J.Q.[Jing-Qian], Wang, P.[Pei], Gao, Z.Y.[Zhi-Yong], Liu, Z.[Zichu], Li, Y.X.[Ya-Xin], Gan, X.Z.[Xiao-Zheng], Liu, Z.N.[Zhong-Nan],
Wood-Leaf Classification of Tree Point Cloud Based on Intensity and Geometric Information,
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Yang, X.[Xuebo], Wang, C.[Cheng], Xi, X.H.[Xiao-Huan], Wang, Y.J.[Ying-Jie], Zhang, Y.[Ying], Zhou, G.Q.[Guo-Qing],
Footprint Size Design of Large-Footprint Full-Waveform LiDAR for Forest and Topography Applications: A Theoretical Study,
GeoRS(59), No. 11, November 2021, pp. 9745-9757.
IEEE DOI 2111
Laser radar, Vegetation mapping, Forestry, Vegetation, Surface emitting lasers, Gravity, Surface topography, topography application BibRef

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Yu, J.W.[Jin-Woo], Yoon, Y.W.[Young-Woong], Baek, W.K.[Won-Kyung], Jung, H.S.[Hyung-Sup],
Forest Vertical Structure Mapping Using Two-Seasonal Optic Images and LiDAR DSM Acquired from UAV Platform through Random Forest, XGBoost, and Support Vector Machine Approaches,
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Johnson, K.M.[Katharine M.], Ouimet, W.B.[William B.], Dow, S.[Samantha], Haverfield, C.[Cheyenne],
Estimating Historically Cleared and Forested Land in Massachusetts, USA, Using Airborne LiDAR and Archival Records,
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Bauer, L.[Luise], Knapp, N.[Nikolai], Fischer, R.[Rico],
Mapping Amazon Forest Productivity by Fusing GEDI Lidar Waveforms with an Individual-Based Forest Model,
RS(13), No. 22, 2021, pp. xx-yy.
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St. Peter, J.[Joseph], Drake, J.[Jason], Medley, P.[Paul], Ibeanusi, V.[Victor],
Forest Structural Estimates Derived Using a Practical, Open-Source Lidar-Processing Workflow,
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Ayrey, E.[Elias], Hayes, D.J.[Daniel J.], Kilbride, J.B.[John B.], Fraver, S.[Shawn], Kershaw, J.A.[John A.], Cook, B.D.[Bruce D.], Weiskittel, A.R.[Aaron R.],
Synthesizing Disparate LiDAR and Satellite Datasets through Deep Learning to Generate Wall-to-Wall Regional Inventories for the Complex, Mixed-Species Forests of the Eastern United States,
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Kay, H.[Heather], Santoro, M.[Maurizio], Cartus, O.[Oliver], Bunting, P.[Pete], Lucas, R.[Richard],
Exploring the Relationship between Forest Canopy Height and Canopy Density from Spaceborne LiDAR Observations,
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Richter, K., Maas, H.G.,
Radiometric enhancement of full-waveform airborne laser scanner data for volumetric representation in environmental applications,
PandRS(183), 2022, pp. 510-524.
Elsevier DOI 2201
Full-waveform airborne laser scanning, Attenuation correction, Waveform history analysis BibRef

Stelling, N., Richter, K.,
Voxel Based Representation Of Full-waveform Airborne Laser Scanner Data For Forestry Applications,
ISPRS16(B8: 755-762).
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Blaszczak-Bak, W.[Wioleta], Janicka, J.[Joanna], Kozakiewicz, T.[Tomasz], Chudzikiewicz, K.[Krystian], Bak, G.[Grzegorz],
Methodology of Calculating the Number of Trees Based on ALS Data for Forestry Applications for the Area of Samlawki Forest District,
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Tijerín-Triviño, J.[Julián], Moreno-Fernández, D.[Daniel], Zavala, M.A.[Miguel A.], Astigarraga, J.[Julen], García, M.[Mariano],
Identifying Forest Structural Types along an Aridity Gradient in Peninsular Spain: Integrating Low-Density LiDAR, Forest Inventory, and Aridity Index,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
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Abdi, O.[Omid], Uusitalo, J.[Jori], Kivinen, V.P.[Veli-Pekka],
Logging Trail Segmentation via a Novel U-Net Convolutional Neural Network and High-Density Laser Scanning Data,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
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Stitt, J.M.[Jessica M.], Hudak, A.T.[Andrew T.], Silva, C.A.[Carlos A.], Vierling, L.A.[Lee A.], Vierling, K.T.[Kerri T.],
Evaluating the Use of Lidar to Discern Snag Characteristics Important for Wildlife,
RS(14), No. 3, 2022, pp. xx-yy.
DOI Link 2202
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Parada-Díaz, J.[Jesús], López, Á.B.F.[Ángel B. Fernández], González, L.A.G.[Luis A. Gómez], del Arco Aguilar, M.J.[Marcelino J.], González-Mancebo, J.M.[Juana María],
Assessing the Usefulness of LiDAR for Monitoring the Structure of a Montane Forest on a Subtropical Oceanic Island,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
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Pagliai, A.[Andrea], Ammoniaci, M.[Marco], Sarri, D.[Daniele], Lisci, R.[Riccardo], Perria, R.[Rita], Vieri, M.[Marco], d'Arcangelo, M.E.M.[Mauro Eugenio Maria], Storchi, P.[Paolo], Kartsiotis, S.P.[Simon-Paolo],
Comparison of Aerial and Ground 3D Point Clouds for Canopy Size Assessment in Precision Viticulture,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203
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Kruper, A.[Ally], McGaughey, R.J.[Robert J.], Crumrine, S.[Sarah], Bormann, B.T.[Bernard T.], Bennett, K.[Keven], Bobsin, C.R.[Courtney R.],
Using Airborne LiDAR to Map Red Alder in the Sappho Long-Term Ecosystem Productivity Study,
RS(14), No. 7, 2022, pp. xx-yy.
DOI Link 2205
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Liu, H.[Hao], Cao, F.[Fuliang], She, G.H.[Guang-Hui], Cao, L.[Lin],
Extrapolation Assessment for Forest Structural Parameters in Planted Forests of Southern China by UAV-LiDAR Samples and Multispectral Satellite Imagery,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
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Han, T.[Tao], Sánchez-Azofeifa, G.A.[Gerardo Arturo],
A Deep Learning Time Series Approach for Leaf and Wood Classification from Terrestrial LiDAR Point Clouds,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
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Fayad, I.[Ibrahim], Baghdadi, N.[Nicolas], Lahssini, K.[Kamel],
An Assessment of the GEDI Lasers' Capabilities in Detecting Canopy Tops and Their Penetration in a Densely Vegetated, Tropical Area,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
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Wu, X.Q.[Xiang-Qian], Shen, X.[Xin], Zhang, Z.N.[Zheng-Nan], Cao, F.[Fuliang], She, G.H.[Guang-Hui], Cao, L.[Lin],
An Advanced Framework for Multi-Scale Forest Structural Parameter Estimations Based on UAS-LiDAR and Sentinel-2 Satellite Imagery in Forest Plantations of Northern China,
RS(14), No. 13, 2022, pp. xx-yy.
DOI Link 2208
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An, L.[Likun], Wang, J.[Jia], Xiong, N.[Nina], Wang, Y.T.[Yu-Tang], You, J.S.[Jia-Shuo], Li, H.[Hao],
Assessment of Permeability Windbreak Forests with Different Porosities Based on Laser Scanning and Computational Fluid Dynamics,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
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Shen, X.Y.[Xing-Yu], Huang, Q.Q.[Qing-Qing], Wang, X.[Xin], Li, J.[Jiang], Xi, B.[Benye],
A Deep Learning-Based Method for Extracting Standing Wood Feature Parameters from Terrestrial Laser Scanning Point Clouds of Artificially Planted Forest,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Dhargay, S.[Sonam], Lyell, C.S.[Christopher S.], Brown, T.P.[Tegan P.], Inbar, A.[Assaf], Sheridan, G.J.[Gary J.], Lane, P.N.J.[Patrick N. J.],
Performance of GEDI Space-Borne LiDAR for Quantifying Structural Variation in the Temperate Forests of South-Eastern Australia,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Zhou, T.[Tian], dos Santos, R.C.[Renato César], Liu, J.D.[Ji-Dong], Lin, Y.C.[Yi-Chun], Fei, W.C.[William Changhao], Fei, S.L.[Song-Lin], Habib, A.[Ayman],
Comparative Evaluation of a Newly Developed Trunk-Based Tree Detection/Localization Strategy on Leaf-Off LiDAR Point Clouds with Varying Characteristics,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208
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Hevia, A.[Andrea], Calzado, A.[Anabel], Alejano, R.[Reyes], Vázquez-Piqué, J.[Javier],
Identification of Old-Growth Mediterranean Forests Using Airborne Laser Scanning and Geostatistical Analysis,
RS(14), No. 16, 2022, pp. xx-yy.
DOI Link 2208
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Sagar, A.[Ankit], Vega, C.[Cédric], Bouriaud, O.[Olivier], Piedallu, C.[Christian], Renaud, J.P.[Jean-Pierre],
Multisource forest inventories: A model-based approach using k-NN to reconcile forest attributes statistics and map products,
PandRS(192), 2022, pp. 175-188.
Elsevier DOI 2209
Multisource forest inventories, Statistical inference, Forest attribute maps, Reliability assessment, LiDAR, Photogrammetry BibRef

Qi, Y.Q.[Yang-Qian], Coops, N.C.[Nicholas C.], Daniels, L.D.[Lori D.], Butson, C.R.[Christopher R.],
Comparing tree attributes derived from quantitative structure models based on drone and mobile laser scanning point clouds across varying canopy cover conditions,
PandRS(192), 2022, pp. 49-65.
Elsevier DOI 2209
Tree attributes, Laser scanning, Drone, SLAM, Canopy cover, Quantitative structure model (QSM) BibRef

Kriese, J.[Jennifer], Hoeser, T.[Thorsten], Asam, S.[Sarah], Kacic, P.[Patrick], da Ponte, E.[Emmanuel], Gessner, U.[Ursula],
Deep Learning on Synthetic Data Enables the Automatic Identification of Deficient Forested Windbreaks in the Paraguayan Chaco,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
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Schroeder, T.A.[Todd A.], Obata, S.[Shingo], Papes, M.[Monica], Branoff, B.[Benjamin],
Evaluating Statewide NAIP Photogrammetric Point Clouds for Operational Improvement of National Forest Inventory Estimates in Mixed Hardwood Forests of the Southeastern U.S.,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
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Powell, E.B.[Elisabeth B.], Laurent, K.A.S.[Kari A. St.], Dubayah, R.[Ralph],
Lidar-Imagery Fusion Reveals Rapid Coastal Forest Loss in Delaware Bay Consistent with Marsh Migration,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Alvites, C.[Cesar], Marchetti, M.[Marco], Lasserre, B.[Bruno], Santopuoli, G.[Giovanni],
LiDAR as a Tool for Assessing Timber Assortments: A Systematic Literature Review,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
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Dayal, K.R.[Karun R.], Durrieu, S.[Sylvie], Lahssini, K.[Kamel], Alleaume, S.[Samuel], Bouvier, M.[Marc], Monnet, J.M.[Jean-Matthieu], Renaud, J.P.[Jean-Pierre], Revers, F.[Frédéric], Renaud, J.P.[Jean-Pierre], Revers, F.[Frédéric],
An investigation into lidar scan angle impacts on stand attribute predictions in different forest environments,
PandRS(193), 2022, pp. 314-338.
Elsevier DOI 2210
Lidar, ABA models, Scan angle, Forest structure, Voxelisation, Vegetation profile, Leaf area index, Forest inventory BibRef

Sumnall, M.J.[Matthew J.], Hill, R.A.[Ross A.], Hinsley, S.A.[Shelley A.],
Towards Forest Condition Assessment: Evaluating Small-Footprint Full-Waveform Airborne Laser Scanning Data for Deriving Forest Structural and Compositional Metrics,
RS(14), No. 20, 2022, pp. xx-yy.
DOI Link 2211
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Li, B.[Bowen], Lu, H.[Hao], Wang, H.[Han], Qi, J.B.[Jian-Bo], Yang, G.[Gang], Pang, Y.[Yong], Dong, H.L.[Hao-Lin], Lian, Y.[Yining],
Terrain-Net: A Highly-Efficient, Parameter-Free, and Easy-to-Use Deep Neural Network for Ground Filtering of UAV LiDAR Data in Forested Environments,
RS(14), No. 22, 2022, pp. xx-yy.
DOI Link 2212
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Sun, Y.[Yusen], Jin, X.[Xingji], Pukkala, T.[Timo], Li, F.[Fengri],
A Comparison of Four Methods for Automatic Delineation of Tree Stands from Grids of LiDAR Metrics,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Budei, B.C.[Brindusa Cristina], St-Onge, B.[Benoît], Fournier, R.A.[Richard A.], Kneeshaw, D.[Daniel],
Effects of Viewing Geometry on Multispectral Lidar-Based Needle-Leaved Tree Species Identification,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Zhang, B.[Bo], Li, X.J.[Xue-Jian], Du, H.Q.[Hua-Qiang], Zhou, G.[Guomo], Mao, F.J.[Fang-Jie], Huang, Z.[Zihao], Zhou, L.[Lv], Xuan, J.[Jie], Gong, Y.L.[Yu-Lin], Chen, C.[Chao],
Estimation of Urban Forest Characteristic Parameters Using UAV-Lidar Coupled with Canopy Volume,
RS(14), No. 24, 2022, pp. xx-yy.
DOI Link 2212
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Trouvé, R.[Raphael], Jiang, R.Z.[Rui-Zhu], Fedrigo, M.[Melissa], White, M.D.[Matt D.], Kasel, S.[Sabine], Baker, P.J.[Patrick J.], Nitschke, C.R.[Craig R.],
Combining Environmental, Multispectral, and LiDAR Data Improves Forest Type Classification: A Case Study on Mapping Cool Temperate Rainforests and Mixed Forests,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Godfroy, J.[Julien], Lejot, J.[Jérôme], Demarchi, L.[Luca], Bizzi, S.[Simone], Michel, K.[Kristell], Piégay, H.[Hervé],
Combining Hyperspectral, LiDAR, and Forestry Data to Characterize Riparian Forests along Age and Hydrological Gradients,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
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Cabral, R.P.[Ricardo Pinheiro], da Silva, G.F.[Gilson Fernandes], de Almeida, A.Q.[André Quintão], Bonilla-Bedoya, S.[Santiago], Dias, H.M.[Henrique Machado], de Mendonça, A.R.[Adriano Ribeiro], Rodrigues, N.M.M.[Nívea Maria Mafra], Valente, C.C.A.[Carem Cristina Araujo], Oliveira, K.[Klisman], Gonçalves, F.G.[Fábio Guimarães], Sarcinelli, T.S.[Tathiane Santi],
Mapping of the Successional Stage of a Secondary Forest Using Point Clouds Derived from UAV Photogrammetry,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
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Hirschmugl, M.[Manuela], Lippl, F.[Florian], Sobe, C.[Carina],
Assessing the Vertical Structure of Forests Using Airborne and Spaceborne LiDAR Data in the Austrian Alps,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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García-Galar, A.[Aitor], Lamelas, M.T.[M. Teresa], Domingo, D.[Darío],
Assessment of Oak Groves Conservation Statuses in Natura 2000 Sacs with Single Photon Lidar and Sentinel-2 Data,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
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Cai, S.S.[Shang-Shu], Yu, S.[Sisi],
Filtering Airborne LiDAR Data in Forested Environments Based on Multi-Directional Narrow Window and Cloth Simulation,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link 2303
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Shinde, R.C.[Rajat C.], Durbha, S.S.[Surya S.],
Deep Convolutional Compressed Sensing-Based Adaptive 3D Reconstruction of Sparse LiDAR Data: A Case Study for Forests,
RS(15), No. 5, 2023, pp. xx-yy.
DOI Link 2303
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Seeley, M.M.[Megan M.], Martin, R.E.[Roberta E.], Vaughn, N.R.[Nicholas R.], Thompson, D.R.[David R.], Dai, J.[Jie], Asner, G.P.[Gregory P.],
Quantifying the Variation in Reflectance Spectra of Metrosideros polymorpha Canopies across Environmental Gradients,
RS(15), No. 6, 2023, pp. 1614.
DOI Link 2304
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Yu, J.W.[Jin-Woo], Jung, H.S.[Hyung-Sup],
Forest Vertical Structure Mapping Using Multi-Seasonal UAV Images and Lidar Data via Modified U-Net Approaches,
RS(15), No. 11, 2023, pp. 2833.
DOI Link 2306
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Wang, J.[Jie], Yao, C.J.[Chun-Jing], Ma, H.C.[Hong-Chao], Xu, J.H.[Jun-Hao], Qian, C.[Chen],
Sample Plots Forestry Parameters Verification and Updating Using Airborne LiDAR Data,
RS(15), No. 12, 2023, pp. xx-yy.
DOI Link 2307
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Luo, W.J.[Wen-Jun], Ma, H.C.[Hong-Chao], Yuan, J.L.[Jia-Lin], Zhang, L.[Liang], Ma, H.[Haichi], Cai, Z.[Zhan], Zhou, W.W.[Wei-Wei],
High-Accuracy Filtering of Forest Scenes Based on Full-Waveform LiDAR Data and Hyperspectral Images,
RS(15), No. 14, 2023, pp. 3499.
DOI Link 2307
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Wu, Y.[Yang], Zhao, R.[Rong], Hu, Q.[Qing], Zhang, Y.[Yujia], Zhang, K.[Kun],
Retrieving Sub-Canopy Terrain from ICESat-2 Data Based on the RNR-DCM Filtering and Erroneous Ground Photons Correction Approach,
RS(15), No. 15, 2023, pp. xx-yy.
DOI Link 2308
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Ambrosino, A.[Antonella], di Benedetto, A.[Alessandro], Fiani, M.[Margherita],
LiDAR Data and HRSI to Evaluate the Mitigating Effect of Forests into Rockfall Risk Analysis Using SOM: Mt San Liberatore Case Study,
RS(15), No. 18, 2023, pp. 4523.
DOI Link 2310
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Diaz-Kloch, N.[Nicolas], Murray, D.L.[Dennis L.],
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Peng, Y.P.[Ye-Ping], Lin, S.D.[Sheng-Dong], Wu, H.K.[Hong-Kun], Cao, G.Z.[Guang-Zhong],
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Yan, X.H.[Xuan-Hao], Chai, G.Q.[Guo-Qi], Han, X.Y.[Xin-Yi], Lei, L.T.[Ling-Ting], Wang, G.[Geng], Jia, X.[Xiang], Zhang, X.L.[Xiao-Li],
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Navarro-Cerrillo, R.M.[Rafael M.], Cedrés, E.P.[Eva Padrón], Cachinero-Vivar, A.M.[Antonio M.], Valeriano, C.[Cristina], Camarero, J.J.[Jesús Julio],
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Neto, B.H.Z.[Bill Herbert Ziegelmaier], Schimalski, M.B.[Marcos Benedito], Liesenberg, V.[Veraldo], Sothe, C.[Camile], Martins-Neto, R.P.[Rorai Pereira], Floriani, M.M.P.[Mireli Moura Pitz],
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Zhang, D.[Dafeng], Král, K.[Kamil], Krucek, M.[Martin], Cushman, K.C., Kellner, J.R.[James R.],
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Novo, A.[Ana], González-Jorge, H.[Higinio], Martínez-Sánchez, J.[Joaquín], Fernández-Alonso, J.M.[José María], Lorenzo, H.[Henrique],
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Campos, M., Litkey, P., Wang, Y., Chen, Y., Hyyti, H., Hyyppä, J., Puttonen, E.,
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Dayal, K.R., Durrieu, S., Alleaume, S., Revers, F., Larmanou, E., Renaud, J.P., Bouvier, M.,
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Vepakomma, U., Cormier, D.,
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Babadi, M., Sattari, M., Iran Pour, S.,
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Chen, Y., Liu, Z., Zhang, W., Qiao, C., Gu, H.,
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Lee, D., Muir, W., Beeston, S., Bates, S., Schofield, S.D., Edwards, M.J., Green, R.D.,
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IVCNZ18(1-6)
IEEE DOI 1902
Vegetation, Forestry, Measurement, Software, Solid modeling, Virtual reality, Trees, Forest, Point Clouds, Photogrammetry BibRef

Fuse, T., Hiramatsu, D., Nakanishi, W.,
Multi-target Detection From Full-waveform Airborne Laser Scanner Using PHD Filter,
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PHD: probability hypothesis density. Forest and vegetation. BibRef

Monnet, J.M., Ginzler, C., Clivaz, J.C.,
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Kalwar, O.P.P.[Om Prakash Prasad], Hussin, Y.A.[Yousif A.], Weir, M.J.C.[Michael J.C.], Karna, Y.K.[Yogendra K.],
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Crespo-Peremarch, P., Ruiz, L.A., Balaguer-Beser, A., Estornell, J.,
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Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Forest Analysis, IFSAR, SAR, Radar .


Last update:Sep 28, 2024 at 17:47:54