24.4.13 Trees, Individual Trees

Chapter Contents (Back)
Trees. Individual Tree. Crowns:
See also Tree Crowns, Crown Shape, Crown Delineation. Often this is range based.
See also Urban Trees, Individual Trees, Street Trees. Related, but more larger areas:
See also Trees, Forest Canopy Analysis.
See also Trees, Forest, Stem Volume, Aboveground Biomass Measurements.
See also Citrus Trees, Orchards, Diseases.
See also Inspection -- Lumber, Logs, Wood.

Kraus, K., Pfeifer, N.,
Determination of terrain models in wooded areas with airborne laser scanner data,
PandRS(53), No. 4, 01 August 1998, pp. 193-203. BibRef 9808

Larsen, M.[Morten], and Rudemo, M.[Mats],
Optimizing templates for finding trees in aerial photographs,
PRL(19), No. 12, 30 October 1998, pp. 1153-1162. BibRef 9810
Earlier:
Using Ray-Traced Templates to Find Individual Trees in Aerial Photographs,
SCIA97(xx-yy)
HTML Version. 9705
BibRef

Larsen, M.[Morten], Rudemo, M.[Mats],
Approximate Bayesian estimation of a 3D point pattern from multiple views,
PRL(25), No. 12, September 2004, pp. 1359-1368.
Elsevier DOI 0409
Combine data from multiple views. Use for tree models. BibRef

Larsen, M.,
Jittered Match Windows Voting for Tree Top Positions in Aerial Photographs,
SCIA99(Remote Sensing). BibRef 9900

Larsen, M., Rudemo, M.,
Estimation of Tree Positions from Aerial Photos,
SSAB97(Photogrammetry) 9703
BibRef

Haering, N.C.[Niels C.], da Vitoria Lobo, N.[Niels],
Features and Classification Methods to Locate Deciduous Trees in Images,
CVIU(75), No. 1/2, July-August 1999, pp. 133-149.
DOI Link Indexing application BibRef 9907

Haering, N.C.[Niels C.], Myles, Z.[Zarina], da Vitoria Lobo, N.[Niels],
Locating Deciduous Trees,
CBAIVL97(18).
IEEE DOI 9706
BibRef

Evans, D.L.[David L.], Roberts, S.D.[Scott D.], McCombs, J.W.[John W.], Harrington, R.L.[Richard L.],
Detection of Regularly Spaced Targets in Small-Footprint LIDAR Data: Research Issues for Consideration,
PhEngRS(67), No. 10, October 2001, pp. 1133-1136. Small-footprint LIDAR systems do not adequately sample tree tops under typical LIDAR mission conditions.
WWW Link. 0201
BibRef

Persson, A., Holmgren, J., and Söderman, U.,
Detecting and Measuring Individual Trees Using an Airborne Laser Scanner,
PhEngRS(68), No. 9, September 2002, pp. 925-932. Watershed segmentation of trees. BibRef 0209

Raber, G.T.[George T.], Jensen, J.R.[John R.], Schill, S.R.[Steven R.], Schuckman, K.[Karen],
Creation of Digital Terrain Models Using an Adaptive Lidar Vegetation Point Removal Process,
PhEngRS(68), No. 12, December 2002, pp. 1307-1316. A method for the automatic extraction of land-cover thematic information directly from lidar data and the use of this information in an adaptive point removal process to extract more accurate bald-earth digital elevation models from lidar data is presented.
WWW Link. 0304
BibRef

Brandtberg, T.[Tomas],
Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidar,
PandRS(61), No. 5, January 2007, pp. 325-340.
Elsevier DOI 0703
Calibration; Forestry; Lidar; Segmentation; Species classification BibRef

Carleer, A., Wolff, E.,
Exploitation of Very High Resolution Satellite Data for Tree Species Identification,
PhEngRS(70), No. 1, January 2004, pp. 135-140. The potential of very high resolution multispectral satellite images for vegetation mapping, primarily deciduous tree species in "monoculture stands," with conventional hard classification processes is presented.
WWW Link. 0403
BibRef

Moffiet, T., Mengersen, K., Witte, C., King, R., Denham, R.,
Airborne laser scanning: Exploratory data analysis indicates potential variables for classification of individual trees or forest stands according to species,
PandRS(59), No. 5, August 2005, pp. 289-309.
Elsevier DOI 0509
BibRef

Hallberg, B., Smith-Jonforsen, G., Ulander, L.M.H.,
Measurements on individual trees using multiple VHF SAR images,
GeoRS(43), No. 10, October 2005, pp. 2261-2269.
IEEE DOI 0510
BibRef

Hosoi, F.[Fumiki], Omasa, K.[Kenji],
Voxel-Based 3-D Modeling of Individual Trees for Estimating Leaf Area Density Using High-Resolution Portable Scanning Lidar,
GeoRS(44), No. 12, December 2006, pp. 3610-3618.
IEEE DOI 0701
BibRef

Wolf, B.M.[Bernd-Michael], Heipke, C.[Christian],
Automatic extraction and delineation of single trees from remote sensing data,
MVA(18), No. 5, October 2007, pp. 317-330.
Springer DOI 0711
BibRef

Straub, B.M., Heipke, C.,
Automatic Extraction of Trees for 3D City Models from Images and Height Data,
Ascona01(267-277). Color infrared and DSM. Hypothesize tree and building regions, local analysis of tree regions. 0201
BibRef

Straub, B.M.[Bernd-M.],
Automatic Extraction of Trees from Aerial Images and Surface Models,
PIA05(xx-yy).
PDF File. 0509
BibRef
Earlier:
Investigation of the MPEG-7 Homogeneuos Texture Descriptor for the Automatic Extraction of Trees,
PCV02(A: 351). 0305
BibRef

Heipke, C.[Christian], Straub, B.M.[Bernd M.],
Automatic Extraction and Updating of Vegetation Areas in GIS from Satellite Imagery,
ISPRSGIS99(167-174). BibRef 9900

Palenichka, R.M.[Roman M.], Zaremba, M.B.[Marek B.],
Multiscale Isotropic Matched Filtering for Individual Tree Detection in LiDAR Images,
GeoRS(45), No. 12, December 2007, pp. 3944-3956.
IEEE DOI 0711
BibRef
Earlier:
Scale-Adaptive Segmentation and Recognition of Individual Trees Based on LiDAR Data,
ICIAR07(1082-1092).
Springer DOI 0708

See also Automatic Extraction of Control Points for the Registration of Optical Satellite and LiDAR Images. BibRef

Kononov, A.A., Ka, M.H.,
Model-Associated Forest Parameter Retrieval Using VHF SAR Data at the Individual Tree Level,
GeoRS(46), No. 1, January 2008, pp. 69-84.
IEEE DOI 0712
BibRef

Teng, C.H.[Chin-Hung], Chen, Y.S.[Yung-Sheng], Hsu, W.H.[Wen-Hsing],
An Approach to Extracting Trunk from an Image,
IEICE(E89-D), No. 4, April 2006, pp. 1596-1600.
DOI Link 0604
Tree trunks. Not for aerial images though. BibRef

Teng, C.H.[Chin-Hung], Chen, Y.S.[Yung-Sheng],
Image-based tree modeling from a few images with very narrow viewing range,
VC(25), No. 4, April 2009, pp. xx-yy.
Springer DOI 0903
BibRef

Hill, R.A., Broughton, R.K.,
Mapping the understorey of deciduous woodland from leaf-on and leaf-off airborne LiDAR data: A case study in lowland Britain,
PandRS(64), No. 2, March 2009, pp. 223-233.
Elsevier DOI 0903
LIDAR; Laser scanning; Forestry; Model; Mapping BibRef

Lu, W.L.[Wei-Lwun], Murphy, K.P., Little, J.J.[James J.], Sheffer, A.[Alla], Fu, H.B.[Hong-Bo],
A Hybrid Conditional Random Field for Estimating the Underlying Ground Surface From Airborne LiDAR Data,
GeoRS(47), No. 8, August 2009, pp. 2913-2922.
IEEE DOI 0907
BibRef

Lu, W.L.[Wei-Lwun], Little, J.J.[James J.], Sheffer, A.[Alla], Fu, H.B.[Hong-Bo],
Deforestation: Extracting 3D Bare-Earth Surface from Airborne LiDAR Data,
CRV08(203-210).
IEEE DOI 0805
BibRef

Reitberger, J., Schnorr, C., Krzystek, P., Stilla, U.,
3D segmentation of single trees exploiting full waveform LIDAR data,
PandRS(64), No. 6, November 2009, pp. 561-574.
Elsevier DOI 1001
BibRef
Earlier:
3D Segmentation of Full Waveform LIDAR Data for Single Tree Detection Using Normalized Cut,
ISPRS08(B3a: 77 ff).
PDF File. 0807
LIDAR; Segmentation; Aerial survey; Clustering; Forestry BibRef

Rentsch, M.[Matthias], Krismann, A.[Alfons], Krzystek, P.[Peter],
Extraction of Non-forest Trees for Biomass Assessment Based on Airborne and Terrestrial LiDAR Data,
PIA11(121-132).
Springer DOI 1110
BibRef

Yao, W., Krzystek, P., Heurich, M.,
Identifying Standing Dead Trees In Forest Areas Based On 3d Single Tree Detection From Full Waveform Lidar Data,
AnnalsPRS(I-7), No. 2012, pp. 359-364.
DOI Link 1209
BibRef

Reitberger, J.[Josef], Heurich, M., Krzystek, P.[Peter], Stilla, U.[Uwe],
Single Tree Detection in Forest Areas with High-Density LIDAR Data,
PIA07(139).
PDF File. 0711
BibRef

Reitberger, J.[Josef], Krzystek, P.[Peter], Stilla, U.[Uwe],
Combined Tree Segmentation and Stem Detection Using Full Waveform Lidar Data,
Laser07(332).
PDF File. 0709
BibRef
Earlier:
Analysis of Full Waveform Lidar Data for Tree Species Classification,
PCV06(xx-yy).
PDF File. 0609
BibRef

Suratno, A.[Agus], Seielstad, C.[Carl], Queen, L.[Lloyd],
Tree species identification in mixed coniferous forest using airborne laser scanning,
PandRS(64), No. 6, November 2009, pp. 683-693.
Elsevier DOI 1001
North America; Conifer; Laser scanning; Intensity; Tree species BibRef

Aksoy, S., Akcay, H.G., Wassenaar, T.,
Automatic Mapping of Linear Woody Vegetation Features in Agricultural Landscapes Using Very High Resolution Imagery,
GeoRS(48), No. 1, January 2010, pp. 511-522.
IEEE DOI 1001
BibRef

Heikkinen, V., Tokola, T., Parkkinen, J., Korpela, I., Jaaskelainen, T.,
Simulated Multispectral Imagery for Tree Species Classification Using Support Vector Machines,
GeoRS(48), No. 3, March 2010, pp. 1355-1364.
IEEE DOI 1003
BibRef

Heikkinen, V., Korpela, I., Tokola, T., Honkavaara, E., Parkkinen, J.,
An SVM Classification of Tree Species Radiometric Signatures Based on the Leica ADS40 Sensor,
GeoRS(49), No. 11, November 2011, pp. 4539-4551.
IEEE DOI 1112
BibRef

Dufva, T., Praks, J., Jarvenpaa, S., Sarvas, J.,
Scattering Model for a Pine Tree Employing VIE With a Broadband MLFMA and Comparison to ICA,
GeoRS(48), No. 3, March 2010, pp. 1119-1127.
IEEE DOI 1003
BibRef

Jaakkola, A.[Anttoni], Hyyppa, J.[Juha], Kukko, A.[Antero], Yu, X.W.[Xiao-Wei], Kaartinen, H.[Harri], Lehtomaki, M.[Matti], Lin, Y.[Yi],
A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements,
PandRS(65), No. 6, November 2010, pp. 514-522.
Elsevier DOI 1101
Laser scanning; Mobile; Unmanned aerial vehicle; Multi-sensor; Multitemporal BibRef

Yu, X.W.[Xiao-Wei], Hyyppa, J.[Juha], Vastaranta, M.[Mikko], Holopainen, M.[Markus], Viitala, R.[Risto],
Predicting individual tree attributes from airborne laser point clouds based on the random forests technique,
PandRS(66), No. 1, January 2011, pp. 28-37.
Elsevier DOI 1101
Laser scanning; Forestry; Prediction; Feature; Detection BibRef

Kononov, A.A., Wyholt, A., Sandberg, G., Ulander, L.M.H.,
Statistical Analysis of VHF-Band Tree Backscattering Using Forest Ground Truth Data and PO Scattering Model,
GeoRS(49), No. 8, August 2011, pp. 3035-3046.
IEEE DOI 1108
BibRef

Soja, M.J., Sandberg, G., Ulander, L.M.H.,
Regression-Based Retrieval of Boreal Forest Biomass in Sloping Terrain Using P-Band SAR Backscatter Intensity Data,
GeoRS(51), No. 5, May 2013, pp. 2646-2665.
IEEE DOI 1305
BibRef

Puttonen, E.[Eetu], Litkey, P.[Paula], Hyyppä, J.[Juha],
Individual Tree Species Classification by Illuminated: Shaded Area Separation,
RS(2), No. 1, January 2010, pp. 19-35.
DOI Link 1203
BibRef
Earlier:
Usability of Sunlit-Shaded Area Separation in Individual Tree Species Classification,
Laser09(311). 0909
BibRef

Vaughn, N., Moskal, L.M., Turnblom, E.,
Tree Species Detection Accuracies Using Discrete Point Lidar and Airborne Waveform Lidar,
RS(4), No. 2, February 2012, pp. 377-403.
DOI Link 1203
BibRef

Blanchard, S., Jakubowski, M., Kelly, M.,
Object-Based Image Analysis of Downed Logs in Disturbed Forested Landscapes Using Lidar,
RS(3), No. 11, November 2011, pp. 2420-2439.
DOI Link 1203
BibRef

Seielstad, C., Stonesifer, C., Rowell, E., Queen, L.,
Deriving Fuel Mass by Size Class in Douglas-fir (Pseudotsuga menziesii) Using Terrestrial Laser Scanning,
RS(3), No. 8, August 2011, pp. 1691-1709.
DOI Link 1203
BibRef

Wang, Y., Hyyppä, J., Liang, X., Kaartinen, H., Yu, X., Lindberg, E., Holmgren, J., Qin, Y., Mallet, C., Ferraz, A., Torabzadeh, H., Morsdorf, F., Zhu, L., Liu, J., Alho, P.,
International Benchmarking of the Individual Tree Detection Methods for Modeling 3-D Canopy Structure for Silviculture and Forest Ecology Using Airborne Laser Scanning,
GeoRS(54), No. 9, September 2016, pp. 5011-5027.
IEEE DOI 1609
ecology BibRef

Kaartinen, H.[Harri], Hyyppä, J.[Juha], Yu, X.W.[Xiao-Wei], Vastaranta, M.[Mikko], Hyyppä, H.[Hannu], Kukko, A.[Antero], Holopainen, M.[Markus], Heipke, C.[Christian], Hirschmugl, M.[Manuela], Morsdorf, F.[Felix], Næsset, E.[Erik], Pitkänen, J.H.[Ju-Ho], Popescu, S.[Sorin], Solberg, S.[Svein], Wolf, B.M.[Bernd Michael], Wu, J.C.[Jee-Cheng],
An International Comparison of Individual Tree Detection and Extraction Using Airborne Laser Scanning,
RS(4), No. 4, April 2012, pp. 950-974.
DOI Link 1202
Award, Remote Sensing, Second. BibRef

Immitzer, M.[Markus], Atzberger, C.[Clement], Koukal, T.[Tatjana],
Tree Species Classification with Random Forest Using Very High Spatial Resolution 8-Band WorldView-2 Satellite Data,
RS(4), No. 9, September 2012, pp. 2661-2693.
DOI Link 1210
BibRef

Immitzer, M.[Markus], Vuolo, F.[Francesco], Atzberger, C.[Clement],
First Experience with Sentinel-2 Data for Crop and Tree Species Classifications in Central Europe,
RS(8), No. 3, 2016, pp. 166.
DOI Link 1604
BibRef

Immitzer, M.[Markus], Atzberger, C.[Clement], Koukal, T.[Tatjana],
Suitability of WorldView-2 data for tree species classification with special emphasis on the four new spectral bands,
PFG(2012), No. 5, 2012, pp. 573-588.
WWW Link. 1211
BibRef

Buddenbaum, H., Stern, O., Stellmes, M., Stoffels, J., Pueschel, P., Hill, J., Werner, W.,
Field Imaging Spectroscopy of Beech Seedlings under Dryness Stress,
RS(4), No. 12, December 2012, pp. 3721-3740.
DOI Link 1211
BibRef

Stern, O.[Oksana], Paschmionka, B.[Barbara], Stoffels, J.[Johannes], Buddenbaum, H.[Henning], Hill, J.[Joachim],
The use of imaging and non-imaging Spectroscopy for the determination of stress phenomena of beech trees,
PFG(2014), No. 1, February 2014, pp. 17-26.
DOI Link 1405
BibRef

Buddenbaum, H.[Henning], Hill, J.[Joachim],
PROSPECT Inversions of Leaf Laboratory Imaging Spectroscopy: A Comparison of Spectral Range and Inversion Technique Influences,
PFG(2015), No. 3, 2013, pp. 231-240.
DOI Link 1506
BibRef

Wang, L.[Lei], Birt, A.G.[Andrew G.], Lafon, C.W.[Charles W.], Cairns, D.M.[David M.], Coulson, R.N.[Robert N.], Tchakerian, M.D.[Maria D.], Xi, W.M.[Wei-Min], Popescu, S.C.[Sorin C.], Guldin, J.M.[James M.],
Computer-Based Synthetic Data to Assess the Tree Delineation Algorithm from Airborne LiDAR Survey,
GeoInfo(17), No. 1, January 2013, pp. 35-61.
WWW Link. 1302
BibRef

Lindberg, E., Holmgren, J., Olofsson, K., Wallerman, J., Olsson, H.,
Estimation of Tree Lists from Airborne Laser Scanning Using Tree Model Clustering and k-MSN Imputation,
RS(5), No. 4, April 2013, pp. 1932-1955.
DOI Link 1305
BibRef

Olofsson, K.[Kenneth], Holmgren, J.[Johan], Olsson, H.[Håkan],
Tree Stem and Height Measurements using Terrestrial Laser Scanning and the RANSAC Algorithm,
RS(6), No. 5, 2014, pp. 4323-4344.
DOI Link 1407
BibRef

Wang, D., Liu, J.H., Wang, J.L., Li, T.,
A Simple Tree Detector Using Laser and Camera Fusion,
Sensors(153), No. 5, May 2013, pp. 137-145.
HTML Version. 1307
BibRef

Jakubowski, M.K.[Marek K.], Li, W.K.[Wen-Kai], Guo, Q.H.[Qing-Hua], Kelly, M.[Maggi],
Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches,
RS(5), No. 9, 2013, pp. 4163-4186.
DOI Link 1310
BibRef

Eysn, L.[Lothar], Pfeifer, N.[Norbert], Ressl, C.[Camillo], Hollaus, M.[Markus], Grafl, A.[Andreas], Morsdorf, F.[Felix],
A Practical Approach for Extracting Tree Models in Forest Environments Based on Equirectangular Projections of Terrestrial Laser Scans,
RS(5), No. 11, 2013, pp. 5424-5448.
DOI Link 1312
BibRef

Deng, S.Q.[Song-Qiu], Katoh, M.[Masato], Guan, Q.W.[Qing-Wei], Yin, N.[Na], Li, M.Y.[Ming-Yang],
Interpretation of Forest Resources at the Individual Tree Level at Purple Mountain, Nanjing City, China, Using WorldView-2 Imagery by Combining GPS, RS and GIS Technologies,
RS(6), No. 1, 2013, pp. 87-110.
DOI Link 1402
BibRef

Deng, S.Q.[Song-Qiu], Katoh, M.[Masato], Guan, Q.W.[Qing-Wei], Yin, N.[Na], Li, M.Y.[Ming-Yang],
Estimating Forest Aboveground Biomass by Combining ALOS PALSAR and WorldView-2 Data: A Case Study at Purple Mountain National Park, Nanjing, China,
RS(6), No. 9, 2014, pp. 7878-7910.
DOI Link 1410
BibRef

Iovan, C., Cournede, P.H., Guyard, T., Bayol, B., Boldo, D., Cord, M.,
Model-Based Analysis-Synthesis for Realistic Tree Reconstruction and Growth Simulation,
GeoRS(52), No. 2, February 2014, pp. 1438-1450.
IEEE DOI 1402
geophysical image processing BibRef

Lahivaara, T., Seppanen, A., Kaipio, J.P., Vauhkonen, J., Korhonen, L., Tokola, T., Maltamo, M.,
Bayesian Approach to Tree Detection Based on Airborne Laser Scanning Data,
GeoRS(52), No. 5, May 2014, pp. 2690-2699.
IEEE DOI 1403
Estimation;forestry;modeling BibRef

Paula-Filho, P.L.[Pedro L.], Oliveira, L.S.[Luiz S.], Nisgoski, S.[Silvana], de Souza Britto Jr., A.[Alceu],
Forest species recognition using macroscopic images,
MVA(25), No. 4, May 2014, pp. 1019-1031.
Springer DOI 1404
BibRef

Vastaranta, M.[Mikko], Saarinen, N.[Ninni], Kankare, V.[Ville], Holopainen, M.[Markus], Kaartinen, H.[Harri], Hyyppä, J.[Juha], Hyyppä, H.[Hannu],
Multisource Single-Tree Inventory in the Prediction of Tree Quality Variables and Logging Recoveries,
RS(6), No. 4, 2014, pp. 3475-3491.
DOI Link 1405
BibRef

Lu, X.C.[Xing-Cheng], Guo, Q.H.[Qing-Hua], Li, W.K.[Wen-Kai], Flanagan, J.[Jacob],
A bottom-up approach to segment individual deciduous trees using leaf-off lidar point cloud data,
PandRS(94), No. 1, 2014, pp. 1-12.
Elsevier DOI 1407
Lidar BibRef

Waser, L.T.[Lars T.], Küchler, M.[Meinrad], Jütte, K.[Kai], Stampfer, T.[Theresia],
Evaluating the Potential of WorldView-2 Data to Classify Tree Species and Different Levels of Ash Mortality,
RS(6), No. 5, 2014, pp. 4515-4545.
DOI Link 1407
BibRef

Aiteanu, F.[Fabian], Klein, R.[Reinhard],
Hybrid tree reconstruction from inhomogeneous point clouds,
VC(30), No. 6-8, June 2014, pp. 763-771.
WWW Link. 1407
BibRef

Xu, Q.[Qing], Hou, Z.Y.[Zheng-Yang], Maltamo, M.[Matti], Tokola, T.[Timo],
Calibration of area based diameter distribution with individual tree based diameter estimates using airborne laser scanning,
PandRS(93), No. 1, 2014, pp. 65-75.
Elsevier DOI 1407
Forestry BibRef

Betbeder, J.[Julie], Nabucet, J.[Jean], Pottier, E.[Eric], Baudry, J.[Jacques], Corgne, S.[Samuel], Hubert-Moy, L.[Laurence],
Detection and Characterization of Hedgerows Using TerraSAR-X Imagery,
RS(6), No. 5, 2014, pp. 3752-3769.
DOI Link 1407
BibRef

Wang, Z.[Zhen], Zhang, L.Q.[Li-Qiang], Fang, T.[Tian], Mathiopoulos, P.T., Qu, H.M.[Hua-Min], Chen, D.[Dong], Wang, Y.B.[Yue-Bin],
A Structure-Aware Global Optimization Method for Reconstructing 3-D Tree Models From Terrestrial Laser Scanning Data,
GeoRS(52), No. 9, September 2014, pp. 5653-5669.
IEEE DOI 1407
geophysical image processing BibRef

Liang, X.L.[Xin-Lian], Jaakkola, A.[Anttoni], Wang, Y.S.[Yun-Sheng], Hyyppä, J.[Juha], Honkavaara, E.[Eija], Liu, J.B.[Jing-Bin], Kaartinen, H.[Harri],
The Use of a Hand-Held Camera for Individual Tree 3D Mapping in Forest Sample Plots,
RS(6), No. 7, 2014, pp. 6587-6603.
DOI Link 1408
BibRef

Luo, J.[Juhua], Ma, R.H.[Rong-Hua], Duan, H.T.[Hong-Tao], Hu, W.P.[Wei-Ping], Zhu, J.[Jinge], Huang, W.J.[Wen-Jiang], Lin, C.[Chen],
A New Method for Modifying Thresholds in the Classification of Tree Models for Mapping Aquatic Vegetation in Taihu Lake with Satellite Images,
RS(6), No. 8, 2014, pp. 7442-7462.
DOI Link 1410
BibRef

Einzmann, K.[Kathrin], Ng, W.T.[Wai-Tim], Immitzer, M.[Markus], Bachmann, M.[Martin], Pinnel, N.[Nicole], Atzberger, C.[Clement],
Method Analysis for Collecting and Processing in-situ Hyperspectral Needle Reflectance Data for Monitoring Norway Spruce,
PFG(2014), No. 5, 2014, pp. 423-434.
DOI Link 1411
BibRef

Zhang, J.J.[Jun-Jie], Sohn, G.[Gunho], Brédif, M.[Mathieu],
A hybrid framework for single tree detection from airborne laser scanning data: A case study in temperate mature coniferous forests in Ontario, Canada,
PandRS(98), No. 1, 2014, pp. 44-57.
Elsevier DOI 1411
LiDAR BibRef

Ko, C.[Connie], Sohn, G.[Gunho], Remmel, T.K.[Tarmo K.], Miller, J.R.[John R.],
Hybrid Ensemble Classification of Tree Genera Using Airborne LiDAR Data,
RS(6), No. 11, 2014, pp. 11225-11243.
DOI Link 1412
BibRef
Earlier: A1, A2, A3, Only:
A Comparitive Study Using Geometric And Vertical Profile Features Derived From Airborne Lidar For Classifying Tree Genera,
AnnalsPRS(I-3), No. 2012, pp. 129-134.
DOI Link 1209

See also Automatic Powerline Scene Classification And Reconstruction Using Airborne Lidar Data. BibRef

Ko, C.[Connie], Sohn, G.[Gunho], Remmel, T.K.[Tarmo K.], Miller, J.R.[John R.],
Maximizing the Diversity of Ensemble Random Forests for Tree Genera Classification Using High Density LiDAR Data,
RS(8), No. 8, 2016, pp. 646.
DOI Link 1609
BibRef

Hernández-Clemente, R.[Rocío], Navarro-Cerrillo, R.M.[Rafael M.], Ramírez, F.J.R.[Francisco J. Romero], Hornero, A.[Alberto], Zarco-Tejada, P.J.[Pablo J.],
A Novel Methodology to Estimate Single-Tree Biophysical Parameters from 3D Digital Imagery Compared to Aerial Laser Scanner Data,
RS(6), No. 11, 2014, pp. 11627-11648.
DOI Link 1412
BibRef

Girma, A.[Atkilt], Skidmore, A.K.[Andrew K.], de Bie, C.A.J.M., Bongers, F.[Frans],
Understanding Boswellia papyrifera tree secondary metabolites through bark spectral analysis,
PandRS(105), No. 1, 2015, pp. 30-37.
Elsevier DOI 1506
Boswellic acid BibRef

Lamprecht, S.[Sebastian], Stoffels, J.[Johannes], Udelhoven, T.[Thomas],
VecTree: Concepts for 3D modelling of deciduous trees from terrestrial Lidar,
PFG(2015), No. 3, 2013, pp. 241-255.
DOI Link 1506
BibRef

Lamprecht, S.[Sebastian], Stoffels, J.[Johannes], Dotzler, S.[Sandra], Haß, E.[Erik], Udelhoven, T.[Thomas],
aTrunk: An ALS-Based Trunk Detection Algorithm,
RS(7), No. 8, 2015, pp. 9975.
DOI Link 1509
BibRef

Graves, S.J.[Sarah J.], Asner, G.P.[Gregory P.], Martin, R.E.[Roberta E.], Anderson, C.B.[Christopher B.], Colgan, M.S.[Matthew S.], Kalantari, L.[Leila], Bohlman, S.A.[Stephanie A.],
Tree Species Abundance Predictions in a Tropical Agricultural Landscape with a Supervised Classification Model and Imbalanced Data,
RS(8), No. 2, 2016, pp. 161.
DOI Link 1603
BibRef

Deng, S.Q.[Song-Qiu], Katoh, M.[Masato],
Interpretation of Forest Resources at the Individual Tree Level in Japanese Conifer Plantations Using Airborne LiDAR Data,
RS(8), No. 3, 2016, pp. 188.
DOI Link 1604
BibRef

Paris, C., Valduga, D., Bruzzone, L.,
A Hierarchical Approach to Three-Dimensional Segmentation of LiDAR Data at Single-Tree Level in a Multilayered Forest,
GeoRS(54), No. 7, July 2016, pp. 4190-4203.
IEEE DOI 1606
Clustering algorithms BibRef

Yang, B.S.[Bi-Sheng], Dai, W.X.[Wen-Xia], Dong, Z.[Zhen], Liu, Y.[Yang],
Automatic Forest Mapping at Individual Tree Levels from Terrestrial Laser Scanning Point Clouds with a Hierarchical Minimum Cut Method,
RS(8), No. 5, 2016, pp. 372.
DOI Link 1606
BibRef

Yang, B.S.[Bi-Sheng], Liu, Y.[Yuan], Liang, F.[Fuxun], Dong, Z.[Zhen],
Using Mobile Laser Scanning Data For Features Extraction Of High Accuracy Driving Maps,
ISPRS16(B3: 433-439).
DOI Link 1610
BibRef

Hauglin, M.[Marius], Ørka, H.O.[Hans Ole],
Discriminating between Native Norway Spruce and Invasive Sitka Spruce: A Comparison of Multitemporal Landsat 8 Imagery, Aerial Images and Airborne Laser Scanner Data,
RS(8), No. 5, 2016, pp. 363.
DOI Link 1606
BibRef

Ballanti, L.[Laurel], Blesius, L.[Leonhard], Hines, E.[Ellen], Kruse, B.[Bill],
Tree Species Classification Using Hyperspectral Imagery: A Comparison of Two Classifiers,
RS(8), No. 6, 2016, pp. 445.
DOI Link 1608
BibRef

Wang, Z., Zhang, L., Fang, T., Tong, X., Mathiopoulos, P.T., Zhang, L., Mei, J.,
A Local Structure and Direction-Aware Optimization Approach for Three-Dimensional Tree Modeling,
GeoRS(54), No. 8, August 2016, pp. 4749-4757.
IEEE DOI 1608
geophysical image processing BibRef

Yang, B.[Bin], Knyazikhin, Y.[Yuri], Lin, Y.[Yi], Yan, K.[Kai], Chen, C.[Chi], Park, T.[Taejin], Choi, S.[Sungho], Mõttus, M.[Matti], Rautiainen, M.[Miina], Myneni, R.B.[Ranga B.], Yan, L.[Lei],
Analyses of Impact of Needle Surface Properties on Estimation of Needle Absorption Spectrum: Case Study with Coniferous Needle and Shoot Samples,
RS(8), No. 7, 2016, pp. 563.
DOI Link 1608
BibRef

Sheeren, D.[David], Fauvel, M.[Mathieu], Josipovic, V.[Veliborka], Lopes, M.[Maïlys], Planque, C.[Carole], Willm, J.[Jérôme], Dejoux, J.F.[Jean-François],
Tree Species Classification in Temperate Forests Using Formosat-2 Satellite Image Time Series,
RS(8), No. 9, 2016, pp. 734.
DOI Link 1610
BibRef

Karasiak, N., Sheeren, D.[David], Fauvel, M.[Mathieu], Willm, J.[Jérôme], Dejoux, J.F.[Jean-François], Monteil, C.,
Mapping tree species of forests in southwest France using Sentinel-2 image time series,
MultiTemp17(1-4)
IEEE DOI 1712
vegetation, SVM-RBF, SWIR bands, Southwest France, VNIR images, forests mapping tree species, gradient boosted trees, Vegetation BibRef

Deng, S.Q.[Song-Qiu], Katoh, M.[Masato], Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Gao, T.[Tian],
Comparison of Tree Species Classifications at the Individual Tree Level by Combining ALS Data and RGB Images Using Different Algorithms,
RS(8), No. 12, 2016, pp. 1034.
DOI Link 1612
BibRef

Hu, X.B.[Xing-Bo], Chen, W.[Wei], Xu, W.Y.[Wei-Yang],
Adaptive Mean Shift-Based Identification of Individual Trees Using Airborne LiDAR Data,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Dash, J.P.[Jonathan P.], Pearse, G.D.[Grant D.], Watt, M.S.[Michael S.], Paul, T.[Thomas],
Combining Airborne Laser Scanning and Aerial Imagery Enhances Echo Classification for Invasive Conifer Detection,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Weinmann, M.[Martin], Weinmann, M.[Michael], Mallet, C.[Clément], Brédif, M.[Mathieu],
A Classification-Segmentation Framework for the Detection of Individual Trees in Dense MMS Point Cloud Data Acquired in Urban Areas,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Nevalainen, O.[Olli], Honkavaara, E.[Eija], Tuominen, S.[Sakari], Viljanen, N.[Niko], Hakala, T.[Teemu], Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Saari, H.[Heikki], Pölönen, I.[Ilkka], Imai, N.N.[Nilton N.], Tommaselli, A.M.G.[Antonio M. G.],
Individual Tree Detection and Classification with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Saarinen, N.[Ninni], Vastaranta, M.[Mikko], Näsi, R.[Roope], Rosnell, T.[Tomi], Hakala, T.[Teemu], Honkavaara, E.[Eija], Wulder, M.A.[Michael A.], Luoma, V.[Ville], Tommaselli, A.M.G.[Antonio M. G.], Imai, N.N.[Nilton N.], Ribeiro, E.A.W.[Eduardo A. W.], Guimarães, R.B.[Raul B.], Holopainen, M.[Markus], Hyyppä, J.[Juha],
Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Lamprecht, S.[Sebastian], Hill, A.[Andreas], Stoffels, J.[Johannes], Udelhoven, T.[Thomas],
A Machine Learning Method for Co-Registration and Individual Tree Matching of Forest Inventory and Airborne Laser Scanning Data,
RS(9), No. 5, 2017, pp. xx-yy.
DOI Link 1706
BibRef
Earlier: Erratum: RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Wang, Y.J.[Ya-Jie], Lu, D.S.[Deng-Sheng],
Mapping Torreya grandis Spatial Distribution Using High Spatial Resolution Satellite Imagery with the Expert Rules-Based Approach,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
Chinese nutmeg tree. BibRef

Rosskopf, E.[Elena], Morhart, C.[Christopher], Nahm, M.[Michael],
Modelling Shadow Using 3D Tree Models in High Spatial and Temporal Resolution,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Jiang, H.[Hao], Chen, S.[Shuisen], Li, D.[Dan], Wang, C.Y.[Chong-Yang], Yang, J.[Ji],
Papaya Tree Detection with UAV Images Using a GPU-Accelerated Scale-Space Filtering Method,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Waser, L.T.[Lars T.], Ginzler, C.[Christian], Rehush, N.[Nataliia],
Wall-to-Wall Tree Type Mapping from Countrywide Airborne Remote Sensing Surveys,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Zhou, T.[Tan], Popescu, S.C.[Sorin C.], Lawing, A.M.[A. Michelle], Eriksson, M.[Marian], Strimbu, B.M.[Bogdan M.], Bürkner, P.C.[Paul C.],
Bayesian and Classical Machine Learning Methods: A Comparison for Tree Species Classification with LiDAR Waveform Signatures,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Chen, S.Y.[Shih-Yu], Lin, C.S.[Chin-Su], Tai, C.H.[Chia-Hui], Chuang, S.J.[Shang-Ju],
Adaptive Window-Based Constrained Energy Minimization for Detection of Newly Grown Tree Leaves,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802
BibRef

Guirado, E.[Emilio], Tabik, S.[Siham], Alcaraz-Segura, D.[Domingo], Cabello, J.[Javier], Herrera, F.[Francisco],
Deep-learning Versus OBIA for Scattered Shrub Detection with Google Earth Imagery: Ziziphus lotus as Case Study,
RS(9), No. 12, 2017, pp. xx-yy.
DOI Link 1802
BibRef

Parkan, M.[Matthew], Tuia, D.[Devis],
Estimating Uncertainty of Point-Cloud Based Single-Tree Segmentation with Ensemble Based Filtering,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Axelsson, A.[Arvid], Lindberg, E.[Eva], Olsson, H.[Håkan],
Exploring Multispectral ALS Data for Tree Species Classification,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef
And: Erratum: RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Persson, M.[Magnus], Lindberg, E.[Eva], Reese, H.[Heather],
Tree Species Classification with Multi-Temporal Sentinel-2 Data,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812
BibRef

Cabo, C.[Carlos], del Pozo, S.[Susana], Rodríguez-Gonzálvez, P.[Pablo], Ordóñez, C.[Celestino], González-Aguilera, D.[Diego],
Comparing Terrestrial Laser Scanning (TLS) and Wearable Laser Scanning (WLS) for Individual Tree Modeling at Plot Level,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

Amiri, N.[Nina], Polewski, P.[Przemyslaw], Heurich, M.[Marco], Krzystek, P.[Peter], Skidmore, A.K.[Andrew K.],
Adaptive stopping criterion for top-down segmentation of ALS point clouds in temperate coniferous forests,
PandRS(141), 2018, pp. 265-274.
Elsevier DOI 1806
ALS 3D point clouds, Single tree segmentation, Quadratic surfaces, Elliptic paraboloid fitting BibRef

Xie, D.H.[Dong-Hui], Wang, X.Y.[Xiang-Yu], Qi, J.B.[Jian-Bo], Chen, Y.M.[Yi-Ming], Mu, X.[Xihan], Zhang, W.[Wuming], Yan, G.J.[Guang-Jian],
Reconstruction of Single Tree with Leaves Based on Terrestrial LiDAR Point Cloud Data,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Heinzel, J.[Johannes], Huber, M.O.[Markus O.],
Constrained Spectral Clustering of Individual Trees in Dense Forest Using Terrestrial Laser Scanning Data,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Chen, W.[Wei], Hu, X.B.[Xing-Bo], Chen, W.[Wen], Hong, Y.F.[Yi-Feng], Yang, M.H.[Min-Hua],
Airborne LiDAR Remote Sensing for Individual Tree Forest Inventory Using Trunk Detection-Aided Mean Shift Clustering Techniques,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Gini, R.[Rossana], Sona, G.[Giovanna], Ronchetti, G.[Giulia], Passoni, D.[Daniele], Pinto, L.[Livio],
Improving Tree Species Classification Using UAS Multispectral Images and Texture Measures,
IJGI(7), No. 8, 2018, pp. xx-yy.
DOI Link 1809
BibRef
Earlier: A1, A4, A5, A2, Only:
Aerial Images from an UAV System: 3D Modeling and Tree Species Classification in a Park Area,
ISPRS12(XXXIX-B1:361-366).
DOI Link 1209
BibRef

Dai, W.X.[Wen-Xia], Yang, B.S.[Bi-Sheng], Dong, Z.[Zhen], Shaker, A.[Ahmed],
A new method for 3D individual tree extraction using multispectral airborne LiDAR point clouds,
PandRS(144), 2018, pp. 400-411.
Elsevier DOI 1809
Multispectral LiDAR, Forest mapping, Point clouds, Feature extraction, Segmentation BibRef

Dong, T.Y.[Tian-Yang], Zhang, J.[Jian], Gao, S.[Sibin], Shen, Y.[Ying], Fan, J.[Jing],
Single-Tree Detection in High-Resolution Remote-Sensing Images Based on a Cascade Neural Network,
IJGI(7), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Yan, W.Q.[Wan-Qian], Guan, H.Y.[Hai-Yan], Cao, L.[Lin], Yu, Y.T.[Yong-Tao], Gao, S.[Sha], Lu, J.Y.[Jian-Yong],
An Automated Hierarchical Approach for Three-Dimensional Segmentation of Single Trees Using UAV LiDAR Data,
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Zielewska-Büttner, K.[Katarzyna], Heurich, M.[Marco], Müller, J.[Jörg], Braunisch, V.[Veronika],
Remotely Sensed Single Tree Data Enable the Determination of Habitat Thresholds for the Three-Toed Woodpecker (Picoides tridactylus),
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Heinzel, J.[Johannes], Ginzler, C.[Christian],
A Single-Tree Processing Framework Using Terrestrial Laser Scanning Data for Detecting Forest Regeneration,
RS(11), No. 1, 2018, pp. xx-yy.
DOI Link 1901
BibRef

Nuijten, R.J.G.[Rik J.G.], Coops, N.C.[Nicholas C.], Goodbody, T.R.H.[Tristan R.H.], Pelletier, G.[Gaetan],
Examining the Multi-Seasonal Consistency of Individual Tree Segmentation on Deciduous Stands Using Digital Aerial Photogrammetry (DAP) and Unmanned Aerial Systems (UAS),
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904
BibRef

Malek, S.[Salim], Miglietta, F.[Franco], Gobakken, T.[Terje], Næsset, E.[Erik], Gianelle, D.[Damiano], Dalponte, M.[Michele],
Optimizing Field Data Collection for Individual Tree Attribute Predictions Using Active Learning Methods,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Wu, X.Q.[Xiang-Qian], Shen, X.[Xin], Cao, L.[Lin], Wang, G.[Guibin], Cao, F.[Fuliang],
Assessment of Individual Tree Detection and Canopy Cover Estimation using Unmanned Aerial Vehicle based Light Detection and Ranging (UAV-LiDAR) Data in Planted Forests,
RS(11), No. 8, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Kansanen, K.[Kasper], Vauhkonen, J.[Jari], Lähivaara, T.[Timo], Seppänen, A.[Aku], Maltamo, M.[Matti], Mehtätalo, L.[Lauri],
Estimating forest stand density and structure using Bayesian individual tree detection, stochastic geometry, and distribution matching,
PandRS(152), 2019, pp. 66-78.
Elsevier DOI 1905
Histogram matching, Forestry, Forest inventory, Airborne laser scanning, Light Detection And Ranging (LiDAR) BibRef

Bolyn, C.[Corentin], Lejeune, P.[Philippe], Michez, A.[Adrien], Latte, N.[Nicolas],
Automated Classification of Trees outside Forest for Supporting Operational Management in Rural Landscapes,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Xiao, W.[Wen], Zaforemska, A.[Aleksandra], Smigaj, M.[Magdalena], Wang, Y.S.[Yun-Sheng], Gaulton, R.[Rachel],
Mean Shift Segmentation Assessment for Individual Forest Tree Delineation from Airborne Lidar Data,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Gollob, C.[Christoph], Ritter, T.[Tim], Wassermann, C.[Clemens], Nothdurft, A.[Arne],
Influence of Scanner Position and Plot Size on the Accuracy of Tree Detection and Diameter Estimation Using Terrestrial Laser Scanning on Forest Inventory Plots,
RS(11), No. 13, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Kükenbrink, D., Hueni, A., Schneider, F.D., Damm, A., Gastellu-Etchegorry, J., Schaepman, M.E., Morsdorf, F.,
Mapping the Irradiance Field of a Single Tree: Quantifying Vegetation-Induced Adjacency Effects,
GeoRS(57), No. 7, July 2019, pp. 4994-5011.
IEEE DOI 1907
Vegetation mapping, Vegetation, Atmospheric modeling, Solid modeling, Data models, Optical variables measurement, radiative transfer BibRef

Dong, T.Y.[Tian-Yang], Shen, Y.Q.[Yu-Qi], Zhang, J.[Jian], Ye, Y.[Yang], Fan, J.[Jing],
Progressive Cascaded Convolutional Neural Networks for Single Tree Detection with Google Earth Imagery,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908
BibRef

Strimbu, B.M.[Bogdan M.], Qi, C.[Chu], Sessions, J.[John],
Accurate Geo-Referencing of Trees with No or Inaccurate Terrestrial Location Devices,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Du, S.L.[Sheng-Lan], Lindenbergh, R.[Roderik], Ledoux, H.[Hugo], Stoter, J.[Jantien], Nan, L.L.[Liang-Liang],
AdTree: Accurate, Detailed, and Automatic Modelling of Laser-Scanned Trees,
RS(11), No. 18, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Yang, Q.[Qiuli], Su, Y.J.[Yan-Jun], Jin, S.C.[Shi-Chao], Kelly, M.[Maggi], Hu, T.Y.[Tian-Yu], Ma, Q.[Qin], Li, Y.[Yumei], Song, S.L.[Shi-Lin], Zhang, J.[Jing], Xu, G.C.[Guang-Cai], Wei, J.X.[Jian-Xin], Guo, Q.H.[Qing-Hua],
The Influence of Vegetation Characteristics on Individual Tree Segmentation Methods with Airborne LiDAR Data,
RS(11), No. 23, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Hamraz, H.[Hamid], Jacobs, N.B.[Nathan B.], Contreras, M.A.[Marco A.], Clark, C.H.[Chase H.],
Deep learning for conifer/deciduous classification of airborne LiDAR 3D point clouds representing individual trees,
PandRS(158), 2019, pp. 219-230.
Elsevier DOI 1912
Remote sensing, Convolutional neural network, Representation engineering, Unbalanced training data, Mislabel correction BibRef

Williams, J., Schönlieb, C.B.[Carola-Bibiane], Swinfield, T., Lee, J., Cai, X., Qie, L., Coomes, D.A.,
3D Segmentation of Trees Through a Flexible Multiclass Graph Cut Algorithm,
GeoRS(58), No. 2, February 2020, pp. 754-776.
IEEE DOI 2001
Vegetation, Forestry, Biomass, Clustering algorithms, Laser radar, Geometry, Biomass, vegetation mapping BibRef

Yan, W.Q.[Wan-Qian], Guan, H.Y.[Hai-Yan], Cao, L.[Lin], Yu, Y.T.[Yong-Tao], Li, C.[Cheng], Lu, J.Y.[Jian-Yong],
A self-adaptive mean shift tree-segmentation method Using UAV LiDAR data,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Chen, W.[Wei], Xiang, H.B.[Hai-Bing], Moriya, K.[Kazuyuki],
Individual Tree Position Extraction and Structural Parameter Retrieval Based on Airborne LiDAR Data: Performance Evaluation and Comparison of Four Algorithms,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
BibRef

Jurado, J.M., Ramos, M.I., Enríquez, C., Feito, F.R.,
The Impact of Canopy Reflectance on the 3D Structure of Individual Trees in a Mediterranean Forest,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Chaves, P.P.[Pablo Pérez], Zuquim, G.[Gabriela], Ruokolainen, K.[Kalle], van Doninck, J.[Jasper], Kalliola, R.[Risto], Gómez, E.R.[Elvira Rivero], Tuomisto, H.[Hanna],
Mapping Floristic Patterns of Trees in Peruvian Amazonia Using Remote Sensing and Machine Learning,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Stupariu, M.S.[Mihai-Sorin], Plesoianu, A.I.[Alin-Ionut], Patru-Stupariu, I.[Ileana], Fürst, C.[Christine],
A Method for Tree Detection Based on Similarity with Geometric Shapes of 3D Geospatial Data,
IJGI(9), No. 5, 2020, pp. xx-yy.
DOI Link 2005
BibRef

Bennett, G.[Guy], Hardy, A.[Andy], Bunting, P.[Pete], Morgan, P.[Philippe], Fricker, A.[Andrew],
A Transferable and Effective Method for Monitoring Continuous Cover Forestry at the Individual Tree Level Using UAVs,
RS(12), No. 13, 2020, pp. xx-yy.
DOI Link 2007
BibRef

Belcore, E.[Elena], Wawrzaszek, A.[Anna], Wozniak, E.[Edyta], Grasso, N.[Nives], Piras, M.[Marco],
Individual Tree Detection from UAV Imagery Using Hölder Exponent,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Pulido, D.[Dagoberto], Salas, J.[Joaquín], Rös, M.[Matthias], Puettmann, K.[Klaus], Karaman, S.[Sertac],
Assessment of Tree Detection Methods in Multispectral Aerial Images,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
BibRef

Hovi, A.[Aarne], Forsström, P.[Petri], Ghielmetti, G.[Giulia], Schaepman, M.E.[Michael E.], Rautiainen, M.[Miina],
Empirical validation of photon recollision probability in single crowns of tree seedlings,
PandRS(169), 2020, pp. 57-72.
Elsevier DOI 2011
BibRef
And: Corrigendum: PandRS(178), 2021, pp. 135.
Elsevier DOI 2108
Multiangular, Reflectance model, Radiative transfer modeling, Spectral invariants, -theory, Escape probability BibRef

Liang, X.M.[Xing-Ming], Liu, Q.H.M.[Quan-Hua Mark],
Applying Deep Learning to Clear-Sky Radiance Simulation for VIIRS with Community Radiative Transfer Model: Part 1: Develop AI-Based Clear-Sky Mask,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef
And:
Applying Deep Learning to Clear-Sky Radiance Simulation for VIIRS with Community Radiative Transfer Model: Part 2: Model Architecture and Assessment,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef
And: Erratum RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Ai, M.Y.[Ming-Yao], Yao, Y.[Yuan], Hu, Q.W.[Qing-Wu], Wang, Y.[Yue], Wang, W.[Wei],
An Automatic Tree Skeleton Extraction Approach Based on Multi-View Slicing Using Terrestrial LiDAR Scans Data,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Gallardo-Salazar, J.L.[José Luis], Pompa-García, M.[Marín],
Detecting Individual Tree Attributes and Multispectral Indices Using Unmanned Aerial Vehicles: Applications in a Pine Clonal Orchard,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012
BibRef

Hui, Z.Y.[Zhen-Yang], Jin, S.G.[Shuang-Gen], Li, D.J.[Da-Jun], Ziggah, Y.Y.[Yao Yevenyo], Liu, B.[Bo],
Individual Tree Extraction from Terrestrial LiDAR Point Clouds Based on Transfer Learning and Gaussian Mixture Model Separation,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Hui, Z.Y.[Zhen-Yang], Jin, S.G.[Shuang-Gen], Xia, Y.P.[Yuan-Ping], Wang, L.Y.[Le-Yang], Yevenyo Ziggah, Y.[Yao], Cheng, P.G.[Peng-Gen],
Wood and leaf separation from terrestrial LiDAR point clouds based on mode points evolution,
PandRS(178), 2021, pp. 219-239.
Elsevier DOI 2108
Terrestrial LiDAR point clouds, Wood and leaf separation, Mean shift, Mode points, Evolution BibRef

Dersch, S.[Sebastian], Heurich, M.[Marco], Krueger, N.[Nina], Krzystek, P.[Peter],
Combining graph-cut clustering with object-based stem detection for tree segmentation in highly dense airborne lidar point clouds,
PandRS(172), 2021, pp. 207-222.
Elsevier DOI 2101
Single tree segmentation, Stem detection, Graph-cut, Stopping criterion, Dense point cloud, Lidar BibRef

Latella, M.[Melissa], Sola, F.[Fabio], Camporeale, C.[Carlo],
A Density-Based Algorithm for the Detection of Individual Trees from LiDAR Data,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef

Nguyen, H.T.[Ha Trang], Caceres, M.L.L.[Maximo Larry Lopez], Moritake, K.[Koma], Kentsch, S.[Sarah], Shu, H.[Hase], Diez, Y.[Yago],
Individual Sick Fir Tree (Abies mariesii) Identification in Insect Infested Forests by Means of UAV Images and Deep Learning,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101
BibRef
And: Correction: RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Xia, S.B.[Shao-Bo], Chen, D.[Dong], Peethambaran, J.[Jiju], Wang, P.[Pu], Xu, S.[Sheng],
Point Cloud Inversion: A Novel Approach for the Localization of Trees in Forests from TLS Data,
RS(13), No. 3, 2021, pp. xx-yy.
DOI Link 2102
BibRef

Xu, W.B.[Wen-Bing], Deng, S.[Susu], Liang, D.[Dan], Cheng, X.J.[Xiao-Jun],
A Crown Morphology-Based Approach to Individual Tree Detection in Subtropical Mixed Broadleaf Urban Forests Using UAV LiDAR Data,
RS(13), No. 7, 2021, pp. xx-yy.
DOI Link 2104
BibRef

Zhu, R.N.[Ruo-Ning], Guo, Z.Q.[Zheng-Qi], Zhang, X.L.[Xiao-Li],
Forest 3D Reconstruction and Individual Tree Parameter Extraction Combining Close-Range Photo Enhancement and Feature Matching,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Belcore, E.[Elena], Pittarello, M.[Marco], Lingua, A.M.[Andrea Maria], Lonati, M.[Michele],
Mapping Riparian Habitats of Natura 2000 Network (91E0*, 3240) at Individual Tree Level Using UAV Multi-Temporal and Multi-Spectral Data,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105
BibRef

Pontoglio, E.[Emanuele], Dabove, P.[Paolo], Grasso, N.[Nives], Lingua, A.M.[Andrea Maria],
Automatic Features Detection in a Fluvial Environment through Machine Learning Techniques Based on UAVs Multispectral Data,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110
BibRef

Parmehr, E.G.[Ebadat Ghanbari], Amati, M.[Marco],
Individual Tree Canopy Parameters Estimation Using UAV-Based Photogrammetric and LiDAR Point Clouds in an Urban Park,
RS(13), No. 11, 2021, pp. xx-yy.
DOI Link 2106
BibRef

Zamboni, P.[Pedro], Junior, J.M.[José Marcato], de Andrade Silva, J.[Jonathan], Miyoshi, G.T.[Gabriela Takahashi], Matsubara, E.T.[Edson Takashi], Nogueira, K.[Keiller], Gonçalves, W.N.[Wesley Nunes],
Benchmarking Anchor-Based and Anchor-Free State-of-the-Art Deep Learning Methods for Individual Tree Detection in RGB High-Resolution Images,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Kolendo, L.[Lukasz], Kozniewski, M.[Marcin], Ksepko, M.[Marek], Chmur, S.[Szymon], Neroj, B.[Bozydar],
Parameterization of the Individual Tree Detection Method Using Large Dataset from Ground Sample Plots and Airborne Laser Scanning for Stands Inventory in Coniferous Forest,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107
BibRef

Tan, K.[Kai], Zhang, W.G.[Wei-Guo], Dong, Z.[Zhen], Cheng, X.L.[Xiao-Long], Cheng, X.J.[Xiao-Jun],
Leaf and Wood Separation for Individual Trees Using the Intensity and Density Data of Terrestrial Laser Scanners,
GeoRS(59), No. 8, August 2021, pp. 7038-7050.
IEEE DOI 2108
Vegetation, Estimation, Forestry, Surface emitting lasers, Instruments, Reliability, terrestrial laser scanning (TLS) BibRef

Iqbal, I.A.[Irfan A.], Osborn, J.[Jon], Stone, C.[Christine], Lucieer, A.[Arko],
A Comparison of ALS and Dense Photogrammetric Point Clouds for Individual Tree Detection in Radiata Pine Plantations,
RS(13), No. 17, 2021, pp. xx-yy.
DOI Link 2109
BibRef

Kaminska, A.[Agnieszka], Lisiewicz, M.[Maciej], Sterenczak, K.[Krzysztof],
Single Tree Classification Using Multi-Temporal ALS Data and CIR Imagery in Mixed Old-Growth Forest in Poland,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112
BibRef

Rodríguez-Puerta, F.[Francisco], Gómez-García, E.[Esteban], Martín-García, S.[Saray], Pérez-Rodríguez, F.[Fernando], Prada, E.[Eva],
UAV-Based LiDAR Scanning for Individual Tree Detection and Height Measurement in Young Forest Permanent Trials,
RS(14), No. 1, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Yu, K.Y.[Kun-Yong], Hao, Z.B.[Zhen-Bang], Post, C.J.[Christopher J.], Mikhailova, E.A.[Elena A.], Lin, L.[Lili], Zhao, G.[Gejin], Tian, S.F.[Shang-Feng], Liu, J.[Jian],
Comparison of Classical Methods and Mask R-CNN for Automatic Tree Detection and Mapping Using UAV Imagery,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Ma, K.[Kaisen], Chen, Z.X.[Zhen-Xiong], Fu, L.[Liyong], Tian, W.L.[Wan-Li], Jiang, F.[Fugen], Yi, J.[Jing], Du, Z.[Zhi], Sun, H.[Hua],
Performance and Sensitivity of Individual Tree Segmentation Methods for UAV-LiDAR in Multiple Forest Types,
RS(14), No. 2, 2022, pp. xx-yy.
DOI Link 2201
BibRef

Zhang, C.[Chong], Zhou, J.W.[Jia-Wei], Wang, H.[Huiwen], Tan, T.Y.[Tian-Yi], Cui, M.C.[Meng-Chen], Huang, Z.[Zilu], Wang, P.[Pei], Zhang, L.[Li],
Multi-Species Individual Tree Segmentation and Identification Based on Improved Mask R-CNN and UAV Imagery in Mixed Forests,
RS(14), No. 4, 2022, pp. xx-yy.
DOI Link 2202
BibRef

Suwardhi, D.[Deni], Fauzan, K.N.[Kamal Nur], Harto, A.B.[Agung Budi], Soeksmantono, B.[Budhy], Virtriana, R.[Riantini], Murtiyoso, A.[Arnadi],
3D Modeling of Individual Trees from LiDAR and Photogrammetric Point Clouds by Explicit Parametric Representations for Green Open Space (GOS) Management,
IJGI(11), No. 3, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Cao, W.[Wei], Wu, J.Y.[Jia-Yi], Shi, Y.F.[Yu-Feng], Chen, D.[Dong],
Restoration of Individual Tree Missing Point Cloud Based on Local Features of Point Cloud,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Ramtvedt, E.N.[Eirik Næsset], Gobakken, T.[Terje], Næsset, E.[Erik],
Fine-Spatial Boreal-Alpine Single-Tree Albedo Measured by UAV: Experiences and Challenges,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204
BibRef

Morgan, C.J.[Carli J.], Powers, M.[Matthew], Strimbu, B.M.[Bogdan M.],
Estimating Tree Defects with Point Clouds Developed from Active and Passive Sensors,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

de Paula Pires, R.[Raul], Olofsson, K.[Kenneth], Persson, H.J.[Henrik Jan], Lindberg, E.[Eva], Holmgren, J.[Johan],
Individual tree detection and estimation of stem attributes with mobile laser scanning along boreal forest roads,
PandRS(187), 2022, pp. 211-224.
Elsevier DOI 2205
Stem diameter, Stem volume, Car-mounted, Automatic stem detection, MLS BibRef

Lisiewicz, M.[Maciej], Kaminska, A.[Agnieszka], Kraszewski, B.[Bartlomiej], Sterenczak, K.[Krzysztof],
Correcting the Results of CHM-Based Individual Tree Detection Algorithms to Improve Their Accuracy and Reliability,
RS(14), No. 8, 2022, pp. xx-yy.
DOI Link 2205
BibRef

Hui, Z.Y.[Zhen-Yang], Cai, Z.C.[Zhao-Chen], Liu, B.[Bo], Li, D.J.[Da-Jun], Liu, H.[Hua], Li, Z.X.[Zhuo-Xuan],
A Self-Adaptive Optimization Individual Tree Modeling Method for Terrestrial LiDAR Point Clouds,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Sun, J.Q.[Jing-Qian], Wang, P.[Pei], Li, R.H.[Rong-Hao], Zhou, M.[Mei], Wu, Y.H.[Yu-Han],
Fast Tree Skeleton Extraction Using Voxel Thinning Based on Tree Point Cloud,
RS(14), No. 11, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Chen, Q.D.[Qing-Da], Gao, T.[Tian], Zhu, J.J.[Jiao-Jun], Wu, F.[Fayun], Li, X.F.[Xiu-Fen], Lu, D.L.[De-Liang], Yu, F.Y.[Feng-Yuan],
Individual Tree Segmentation and Tree Height Estimation Using Leaf-Off and Leaf-On UAV-LiDAR Data in Dense Deciduous Forests,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Maldonado, C.[Carlos], Mora-Poblete, F.[Freddy], Echeverria, C.[Cristian], Baettig, R.[Ricardo], Torres-Díaz, C.[Cristian], Contreras-Soto, R.I.[Rodrigo Iván], Heidari, P.[Parviz], Lobos, G.A.[Gustavo Adolfo], Teixeira do Amaral Júnior, A.[Antônio],
A Neural Network-Based Spectral Approach for the Assignment of Individual Trees to Genetically Differentiated Subpopulations,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
BibRef

Sparks, A.M.[Aaron M.], Corrao, M.V.[Mark V.], Smith, A.M.S.[Alistair M. S.],
Cross-Comparison of Individual Tree Detection Methods Using Low and High Pulse Density Airborne Laser Scanning Data,
RS(14), No. 14, 2022, pp. xx-yy.
DOI Link 2208
BibRef

Carpenter, J.[Joshua], Jung, J.[Jinha], Oh, S.C.[Sung-Chan], Hardiman, B.[Brady], Fei, S.L.[Song-Lin],
An Unsupervised Canopy-to-Root Pathing (UCRP) Tree Segmentation Algorithm for Automatic Forest Mapping,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Spadavecchia, C.[Claudio], Belcore, E.[Elena], Piras, M.[Marco], Kobal, M.[Milan],
An Automatic Individual Tree 3D Change Detection Method for Allometric Parameters Estimation in Mixed Uneven-Aged Forest Stands from ALS Data,
RS(14), No. 18, 2022, pp. xx-yy.
DOI Link 2209
BibRef

Ning, X.J.[Xiao-Juan], Ma, Y.[Yishu], Hou, Y.Y.[Yuan-Yuan], Lv, Z.Y.[Zhi-Yong], Jin, H.Y.[Hai-Yan], Wang, Y.H.[Ying-Hui],
Semantic Segmentation Guided Coarse-to-Fine Detection of Individual Trees from MLS Point Clouds Based on Treetop Points Extraction and Radius Expansion,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210
BibRef

Luo, M.[Meng], Tian, Y.[Yanan], Zhang, S.W.[Sheng-Wei], Huang, L.[Lei], Wang, H.Q.[Hui-Qiang], Liu, Z.Q.[Zhi-Qiang], Yang, L.[Lin],
Individual Tree Detection in Coal Mine Afforestation Area Based on Improved Faster RCNN in UAV RGB Images,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Brodic, N.[Nenad], Cvijetinovic, Ž.[Željko], Milenkovic, M.[Milutin], Kovacevic, J.[Jovan], Stancic, N.[Nikola], Mitrovic, M.[Momir], Mihajlovic, D.[Dragan],
Refinement of Individual Tree Detection Results Obtained from Airborne Laser Scanning Data for a Mixed Natural Forest,
RS(14), No. 21, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Zhang, Z.Y.[Zhen-Yu], Wang, J.[Jian], Li, Z.Y.[Zhi-Yuan], Zhao, Y.L.[You-Long], Wang, R.S.[Rui-Sheng], Habib, A.[Ayman],
Optimization Method of Airborne LiDAR Individual Tree Segmentation Based on Gaussian Mixture Model,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Xi, Z.X.[Zhou-Xin], Hopkinson, C.[Chris],
3D Graph-Based Individual-Tree Isolation (Treeiso) from Terrestrial Laser Scanning Point Clouds,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
BibRef

Wang, Z.C.[Zhi-Chao], Lu, X.[Xin], An, F.[Feng], Zhou, L.J.[Li-Jun], Wang, X.J.[Xiang-Jun], Wang, Z.H.[Zhi-Hao], Zhang, H.Q.[Huai-Qing], Yun, T.[Ting],
Integrating Real Tree Skeleton Reconstruction Based on Partial Computational Virtual Measurement (CVM) with Actual Forest Scenario Rendering: A Solid Step Forward for the Realization of the Digital Twins of Trees and Forests,
RS(14), No. 23, 2022, pp. xx-yy.
DOI Link 2212
3D models of tree BibRef

Lowe, T.[Thomas], Pinskier, J.[Joshua],
Tree Reconstruction Using Topology Optimisation,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301
BibRef
And: Correction: RS(15), No. 11, 2023, pp. 2739.
DOI Link 2306
3D model of trees. BibRef

Qian, C.[Chen], Yao, C.J.[Chun-Jing], Ma, H.C.[Hong-Chao], Xu, J.H.[Jun-Hao], Wang, J.[Jie],
Tree Species Classification Using Airborne LiDAR Data Based on Individual Tree Segmentation and Shape Fitting,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301
BibRef

Niwa, H.[Hideyuki], Dai, G.[Guihang], Ogawa, M.[Midori], Kamada, M.[Mahito],
Development of a Monitoring Method Using UAVs That Can Detect the Occurrence of Bark Stripping by Deer,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302
BibRef

Wang, F.Y.[Fei-Yu], Bryson, M.[Mitch],
Tree Segmentation and Parameter Measurement from Point Clouds Using Deep and Handcrafted Features,
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

Wang, Z.[Zhen], Li, P.[Pu], Cui, Y.C.[Yuan-Cheng], Lei, S.[Shuowen], Kang, Z.Z.[Zhi-Zhong],
Automatic Detection of Individual Trees in Forests Based on Airborne LiDAR Data with a Tree Region-Based Convolutional Neural Network (RCNN),
RS(15), No. 4, 2023, pp. xx-yy.
DOI Link 2303
BibRef

xo Ning, X.J.[Xiao-Juan], Ma, Y.[Yishu], Hou, Y.Y.[Yuan-Yuan], Lv, Z.Y.[Zhi-Yong], Jin, H.Y.[Hai-Yan], Wang, Z.[Zengbo], Wang, Y.H.[Ying-Hui],
Trunk-Constrained and Tree Structure Analysis Method for Individual Tree Extraction from Scanned Outdoor Scenes,
RS(15), No. 6, 2023, pp. 1567.
DOI Link 2304
BibRef

Pu, Y.[Yihan], Xu, D.D.[Dan-Dan], Wang, H.B.[Hao-Bin], Li, X.[Xin], Xu, X.[Xia],
A New Strategy for Individual Tree Detection and Segmentation from Leaf-on and Leaf-off UAV-LiDAR Point Clouds Based on Automatic Detection of Seed Points,
RS(15), No. 6, 2023, pp. 1619.
DOI Link 2304
BibRef

Balestra, M.[Mattia], Tonelli, E.[Enrico], Vitali, A.[Alessandro], Urbinati, C.[Carlo], Frontoni, E.[Emanuele], Pierdicca, R.[Roberto],
Geomatic Data Fusion for 3D Tree Modeling: The Case Study of Monumental Chestnut Trees,
RS(15), No. 8, 2023, pp. 2197.
DOI Link 2305
BibRef

Xia, K.[Kai], Li, C.[Cheng], Yang, Y.[Yinhui], Deng, S.[Susu], Feng, H.L.[Hai-Lin],
Study on Single-Tree Extraction Method for Complex RGB Point Cloud Scenes,
RS(15), No. 10, 2023, pp. xx-yy.
DOI Link 2306
BibRef

Kleinsmann, J.[Jasper], Verbesselt, J.[Jan], Kooistra, L.[Lammert],
Monitoring Individual Tree Phenology in a Multi-Species Forest Using High Resolution UAV Images,
RS(15), No. 14, 2023, pp. 3599.
DOI Link 2307
BibRef

Mao, Z.H.[Zhi-Hui], Lu, Z.[Zhuo], Wu, Y.J.[Yan-Jie], Deng, L.[Lei],
DBH Estimation for Individual Tree: Two-Dimensional Images or Three-Dimensional Point Clouds?,
RS(15), No. 16, 2023, pp. 4116.
DOI Link 2309
BibRef

Sun, J.J.[Jing-Jing], Lin, Y.[Yi],
Assessing the Allometric Scaling of Vectorized Branch Lengths of Trees with Terrestrial Laser Scanning and Quantitative Structure Modeling: A Case Study in Guyana,
RS(15), No. 20, 2023, pp. 5005.
DOI Link 2310
BibRef

Jayathunga, S.[Sadeepa], Pearse, G.D.[Grant D.], Watt, M.S.[Michael S.],
Unsupervised Methodology for Large-Scale Tree Seedling Mapping in Diverse Forestry Settings Using UAV-Based RGB Imagery,
RS(15), No. 22, 2023, pp. 5276.
DOI Link 2311
BibRef

Kwon, R.[Ryoungseob], Ryu, Y.[Youngryel], Yang, T.[Tackang], Zhong, Z.L.[Zi-Long], Im, J.[Jungho],
Merging multiple sensing platforms and deep learning empowers individual tree mapping and species detection at the city scale,
PandRS(206), 2023, pp. 201-221.
Elsevier DOI Code:
WWW Link. 2312
Urban trees mapping, Tree species detection, Multi-modal deep learning, Computer vision BibRef

Wang, J.S.[Jian-Sen], Zhang, H.Q.[Huai-Qing], Liu, Y.[Yang], Zhang, H.C.[Hua-Cong], Zheng, D.P.[Dong-Ping],
Tree-Level Chinese Fir Detection Using UAV RGB Imagery and YOLO-DCAM,
RS(16), No. 2, 2024, pp. 335.
DOI Link 2402
BibRef

Liu, Y.[Yuchan], Chen, D.[Dong], Fu, S.[Shihan], Mathiopoulos, P.T.[Panagiotis Takis], Sui, M.M.[Ming-Ming], Na, J.M.[Jia-Ming], Peethambaran, J.[Jiju],
Segmentation of Individual Tree Points by Combining Marker-Controlled Watershed Segmentation and Spectral Clustering Optimization,
RS(16), No. 4, 2024, pp. 610.
DOI Link 2402
BibRef

Fu, Y.[Yuwen], Niu, Y.F.[Yi-Fang], Wang, L.[Li], Li, W.[Wang],
Individual-Tree Segmentation from UAV-LiDAR Data Using a Region-Growing Segmentation and Supervoxel-Weighted Fuzzy Clustering Approach,
RS(16), No. 4, 2024, pp. 608.
DOI Link 2402
BibRef

Yu, J.[Jiao], Lei, L.[Lei], Li, Z.H.[Zhen-Hong],
Individual Tree Segmentation Based on Seed Points Detected by an Adaptive Crown Shaped Algorithm Using UAV-LiDAR Data,
RS(16), No. 5, 2024, pp. 825.
DOI Link 2403
BibRef

Huang, H.Y.[Hong-Yu], Tian, G.J.[Guo-Ji], Chen, C.C.[Chong-Cheng],
Evaluating the Point Cloud of Individual Trees Generated from Images Based on Neural Radiance Fields (NeRF) Method,
RS(16), No. 6, 2024, pp. 967.
DOI Link 2403
BibRef

Proctor, C.[Cameron], Leu, N.[Nam], Wang, B.[Bin],
The Physiology of Betula glandusa on Two Sunny Summer Days in the Arctic and Linkages with Optical Imagery,
RS(16), No. 12, 2024, pp. 2160.
DOI Link 2406
dwarf birch. BibRef

Li, Y.[Yuan], Liu, Z.H.[Zhi-Hao], Benes, B.[Bedrich], Zhang, X.P.[Xiao-Peng], Guo, J.W.[Jian-Wei],
SVDTree: Semantic Voxel Diffusion for Single Image Tree Reconstruction,
CVPR24(4692-4702)
IEEE DOI 2410
Graphics, Geometry, Computational modeling, Biological system modeling, Semantics BibRef

Nemmaoui, A.[Abderrahim], Aguilar, F.J.[Fernando J.], Aguilar, M.A.[Manuel A.],
Benchmarking of Individual Tree Segmentation Methods in Mediterranean Forest Based on Point Clouds from Unmanned Aerial Vehicle Imagery and Low-Density Airborne Laser Scanning,
RS(16), No. 21, 2024, pp. 3974.
DOI Link 2411
BibRef

Tinkham, W.T.[Wade T.], Woolsey, G.A.[George A.],
Influence of Structure from Motion Algorithm Parameters on Metrics for Individual Tree Detection Accuracy and Precision,
RS(16), No. 20, 2024, pp. 3844.
DOI Link 2411
BibRef

Verhelst, T.E.[Tom E.], Calders, K.[Kim], Burt, A.[Andrew], Demol, M.[Miro], D'hont, B.[Barbara], Nightingale, J.[Joanne], Terryn, L.[Louise], Verbeeck, H.[Hans],
Implications of Pulse Frequency in Terrestrial Laser Scanning on Forest Point Cloud Quality and Individual Tree Structural Metrics,
RS(16), No. 23, 2024, pp. 4560.
DOI Link 2501
BibRef

Hyyppä, M.[Matti], Turppa, T.[Tuomas], Hyyti, H.[Heikki], Yu, X.W.[Xiao-Wei], Handolin, H.[Hannu], Kukko, A.[Antero], Hyyppä, J.[Juha], Virtanen, J.P.[Juho-Pekka],
Concepts Towards Nation-Wide Individual Tree Data and Virtual Forests,
IJGI(13), No. 12, 2024, pp. 424.
DOI Link 2501
BibRef

Li, T.[Ting], Shen, X.[Xin], Zhou, K.[Kai], Cao, L.[Lin],
Estimation of Individual Tree Structure and Wood Density Parameters for Ginkgo biloba Using Terrestrial LiDAR and Resistance Drill Data,
RS(17), No. 1, 2025, pp. 99.
DOI Link 2501
BibRef

Lee, J.J.[Jae Joong], Li, B.S.[Bo-Sheng], Beery, S.[Sara], Huang, J.[Jonathan], Fei, S.[Songlin], Yeh, R.A.[Raymond A.], Benes, B.[Bedrich],
Tree-d Fusion: Simulation-ready Tree Dataset from Single Images with Diffusion Priors,
ECCV24(XLI: 439-460).
Springer DOI 2412
BibRef

Uçar, Z., Akay, A.E.[Abdullah E.],
Using UAV-based 3d Images of Individual Tree Species in Distance Education in Forestry,
SmartCityApp21(533-537).
DOI Link 2201
BibRef

Lange, J.H.[Jan-Hendrik], Andres, B.[Björn],
On the Lifted Multicut Polytope for Trees,
GCPR20(360-372).
Springer DOI 2110
BibRef

Tong, P.[Pinmo], Zhang, X.S.[Xi-Shan], Han, P.C.[Peng-Cheng], Bu, S.H.[Shu-Hui],
Point in: Counting Trees with Weakly Supervised Segmentation Network,
ICPR21(9546-9552)
IEEE DOI 2105
Location awareness, Deep learning, Image segmentation, Annotations, Feature extraction BibRef