22.5.4 Trees, Individual Trees, Tree Crowns

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

Hyyppa, J., Kelle, O., Lehikoinen, M., Inkinen, M.,
A segmentation-based method to retrieve stem volume estimates from 3-D tree height models produced by laser scanners,
GeoRS(39), No. 5, May 2001, pp. 969-975.
IEEE Top Reference. 0106
BibRef

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.
WWW Version. 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.
WWW Version. Indexing application BibRef 9907

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

Zhang, Y.[Yun],
Texture-Integrated Classification of Urban Treed Areas in High-Resolution Color-Infrared Imagery,
PhEngRS(67), No. 12, December 2001, pp. 1359-1366. To effectively extract tree textural features and eliminate noise, use conditional variance detection. It consists of a directional variance detection and a local variance detection.
WWW Version. 0201
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 Version. 0201
BibRef

Gong, P., Sheng, Y., Biging, G.S.,
3D Model-Based Tree Measurement from High-Resolution Aerial Imagery,
PhEngRS(68), No. 11, November 2002, pp. 1203-1212. An interactive 3D model-based tree interpreter is proposed to extract 3D tree parameters such as tree location, tree height, crown depth, crown radius, and crown surface curvature from multi-ocular high-resolution aerial images.
WWW Version. 0304
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

Pouliot, D.A., King, D.J., Bell, F.W., Pitt, D.G.,
Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration,
RSE(82), No. 2-3, October 2002, pp. 322-334.
HTML Version. 0210
BibRef

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 Version. 0304
BibRef

Lévesque, J.[Josée], King, D.J.[Douglas J.],
Spatial analysis of radiometric fractions from high-resolution multispectral imagery for modelling individual tree crown and forest canopy structure and health,
RSE(84), No. 4, 10 April 2003, pp. 589-602.
WWW Version. 0309
BibRef

Brandtberg, T.[Tomas], Warner, T.A.[Timothy A.], Landenberger, R.E.[Rick E.], McGraw, J.B.[James B.],
Detection and analysis of individual leaf-off tree crowns in small footprint, high sampling density lidar data from the eastern deciduous forest in North America,
RSE(85), No. 3, 30 May 2003, pp. 290-303.
WWW Version. 0309
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.
WWW Version. 0703
Calibration; Forestry; Lidar; Segmentation; Species classification BibRef

Warner, T.A.[Timothy A.], Steinmaus, K.[Karen],
Spatial Classification of Orchards and Vineyards with High Spatial Resolution Panchromatic Imagery,
PhEngRS(71), No. 2, February 2005, pp. 179-188. Spatial auto correlation measures are used to classify land cover types with distinct spatial patterns.
WWW Version. 0509
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 Version. 0403
BibRef

Wang, L.[Le], Gong, P.[Peng], Biging, G.S.[Gregory S.],
Individual Tree-Crown Delineation and Treetop Detection in High-Spatial-Resolution Aerial Imagery,
PhEngRS(70), No. 3, March 2004, pp. 351-358. A promising agreement between automatic methods and manual delineation results was achieved in counting the number of trees as well as in delineating tree crowns.
WWW Version. 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.
WWW Version. 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 Link 0510
BibRef

Houldcroft, C.J., Campbell, C.L., Davenport, I.J., Gurney, R.J., Holden, N.,
Measurement of canopy geometry characteristics using LiDAR laser altimetry: a feasibility study,
GeoRS(43), No. 10, October 2005, pp. 2270-2282.
IEEE DOI Link 0510
BibRef

Erikson, M.[Mats], Olofsson, K.[Kenneth],
Comparison of three individual tree crown detection methods,
MVA(16), No. 4, September 2005, pp. 258-265.
Springer DOI Link 0512
BibRef

Erikson, M.[Mats],
Structure-Preserving Segmentation of Individual Tree Crowns by Brownian Motion,
SCIA03(283-289).
WWW Version. 0310
BibRef
Earlier:
Structure-keeping Colour Segmentation of Tree Crowns in Aerial Images,
SCIA01(O-Tu1). 0206
BibRef

Bortolot, Z.J.[Zachary J.], Wynne, R.H.[Randolph H.],
Estimating forest biomass using small footprint LiDAR data: An individual tree-based approach that incorporates training data,
PandRS(59), No. 6, November 2005, pp. 342-360.
WWW Version. 0602
BibRef

Bortolot, Z.J.[Zachary J.],
Using Tree Clusters to Derive Forest Properties from Small Footprint Lidar Data,
PhEngRS(72), No. 12, December 2006, pp. 1389-1398.
WWW Version. 0704
An object-oriented small footprint lidar algorithm that uses properties of tree clusters to predict forest properties. BibRef

Koch, B.[Barbara], Heyder, U.[Ursula], Weinacker, H.[Holger],
Detection of Individual Tree Crowns in Airborne Lidar Data,
PhEngRS(72), No. 4, April 2006, pp. 357-364.
WWW Version. 0610
An approach to delineate tree crowns in mixed and deciduous temperate forests. BibRef

Wang, Y., Weinacker, H.[Holger], Koch, B.[Barbara],
Development of a Procedure for Vertical Structure Analysis and 3D Single Tree Extraction within Forests Based on Lidar Point Cloud,
Laser07(419).
PDF Version. 0709
BibRef

Koch, B.[Barbara],
Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment,
PandRS(65), No. 6, November 2010, pp. 581-590.
Elsevier DOI Link
WWW Version. 1101
Forest biomass mapping; Fullwave laser; Polarimetric SAR interferometry; Hyperspectral data; Multi-sensoral data BibRef

Chen, Q.[Qi], Baldocchi, D.[Dennis], Gong, P.[Peng], Kelly, M.[Maggi],
Isolating Individual Trees in a Savanna Woodland Using Small Footprint Lidar Data,
PhEngRS(72), No. 8, August 2006, pp. 923-392.
WWW Version. 0610
A new method for detecting treetops from lidar data and applying marked-controlled watershed segmentation to the isolation of individual trees. BibRef

Chen, Q.[Qi], Gong, P.[Peng], Baldocchi, D.[Dennis], Tian, Y.Q.[Yong Q.],
Estimating Basal Area and Stem Volume for Individual Trees from Lidar Data,
PhEngRS(73), No. 12, December 2007, pp. 1355-1366.
WWW Version. 0712
A new lidar metric for forest canopy geometric volume for estimating basal area and stem volume on individual trees is tested. 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 Link 0701
BibRef

Hosoi, F.[Fumiki], Omasa, K.[Kenji],
Estimating vertical plant area density profile and growth parameters of a wheat canopy at different growth stages using three-dimensional portable lidar imaging,
PandRS(64), No. 2, March 2009, pp. 151-158.
Elsevier DOI Link
WWW Version. 0903
Carbon stock; Plant area density; Portable scanning lidar; Three-dimensional imaging; Voxel-based canopy profiling BibRef

Hosoi, F.[Fumiki], Omasa, K.[Kenji],
Estimating Vertical Leaf Area Density Profiles of Tree Canopies Using Three-Dimensional Portable Lidar Imaging,
Laser09(152). 0909
BibRef

Shrivastava, R.J.[Rahul J.], Gebelein, J.L.[Jennifer L.],
Land cover classification and economic assessment of citrus groves using remote sensing,
PandRS(61), No. 5, January 2007, pp. 341-353.
WWW Version. 0703
Agriculture; Economy; Citrus Grove Area Estimation; Landsat BibRef

Gougeon, F.A.[François A.], Leckie, D.G.[Donald G.],
The Individual Tree Crown Approach Applied to Ikonos Images of a Coniferous Plantation Area,
PhEngRS(72), No. 11, November 2006, pp. 1287-1297.
WWW Version. 0704
An assessment of the effects of 1m and 4m resolution on the detection, delineation, and classification of individual tree crowns. BibRef

Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Kukko, A.[Antero], Maltamo, M.[Matti], Kaartinen, H.[Harri],
Change Detection Techniques for Canopy Height Growth Measurements Using Airborne Laser Scanner Data,
PhEngRS(72), No. 12, December 2006, pp. 1339-1348.
WWW Version. 0704
The individual tree height growth of Scots pine was estimated from two laser surveys with three different techniques, and the accuracy of the estimation was evaluated with sample trees. BibRef

Solberg, S.[Svein], Naesset, E.[Erik], Bollandsas, O.M.[Ole Martin],
Single Tree Segmentation Using Airborne Laser Scanner Data in a Structurally Heterogeneous Spruce Forest,
PhEngRS(72), No. 12, December 2006, pp. 1369-1378.
WWW Version. 0704
A new method for single tree segmentation and algorithms for estimating crown base height are presented and tested. BibRef

Ørka, H.O., Naesset, E.[Erik], Bollandsås, O.M.[Ole Martin],
Utilizing Airborne Laser Intensity for Tree Species Classification,
Laser07(300).
PDF Version. 0709
BibRef

Rowell, E.[Eric], Seielstad, C.[Carl], Vierling, L.[Lee], Queen, L.[Lloyd], Shepperd, W.[Wayne],
Using Laser Altimetry-based Segmentation to Refine Automated Tree Identification in Managed Forests of the Black Hills, South Dakota,
PhEngRS(72), No. 12, December 2006, pp. 1379-1388.
WWW Version. 0704
A comparison of landscape segmentation techniques, including using a combination laser based canopy height variance/percent canopy cover classification coupled with smoothing decisions to improve automated stem detection using a variable window-size algorithm. 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 Link 0711
BibRef

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 Link 0711
BibRef
Earlier:
Scale-Adaptive Segmentation and Recognition of Individual Trees Based on LiDAR Data,
ICIAR07(1082-1092).
Springer DOI Link 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 Link 0712
BibRef

Ouma, Y.O.[Yashon O.], Tateishi, R.,
Urban-trees extraction from Quickbird imagery using multiscale spectex-filtering and non-parametric classification,
PandRS(63), No. 3, May 2008, pp. 333-351.
WWW Version. 0711
Quickbird; Urban-trees; Multiscale texture; Multiscale spectex-filtering; Non-parametric classification 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.
WWW Version. 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 Link 0903
BibRef

Hallberg, B., Smith-Jonforsen, G., Ulander, L.M.H., Sandberg, G.,
A Physical-Optics Model for Double-Bounce Scattering From Tree Stems Standing on an Undulating Ground Surface,
GeoRS(46), No. 9, September 2008, pp. 2607-2621.
IEEE DOI Link 0810
BibRef

Folkesson, K., Smith-Jonforsen, G., Ulander, L.M.H.,
Model-Based Compensation of Topographic Effects for Improved Stem-Volume Retrieval From CARABAS-II VHF-Band SAR Images,
GeoRS(47), No. 4, April 2009, pp. 1045-1055.
IEEE DOI Link 0903
BibRef

Horváth, P.[Péter], Jermyn, I.H.[Ian H.], Kato, Z.[Zoltan], Zerubia, J.B.[Josiane B.],
A Higher-Order Active Contour Model of a 'Gas of Circles' and its Application to Tree Crown Extraction,
PR(42), No. 5, May 2009, pp. 699-709.
Elsevier DOI Link
WWW Version. 0902
BibRef
Earlier:
An Improved 'Gas of Circles' Higher-Order Active Contour Model and Its Application to Tree Crown Extraction,
ICCVGIP06(152-161).
Springer DOI Link 0612
BibRef
Earlier: A1, A2, A4, A3:
A Higher-Order Active Contour Model for Tree Detection,
ICPR06(II: 130-133).
IEEE DOI Link 0609
See also Higher Order Active Contours. Tree; Crown; Extraction; Aerial image; Higher-order; Active contour; Gas of circles; Prior; Shape BibRef

Horváth, P.[Péter],
A Multispectral Data Model for Higher-Order Active Contours and Its Application to Tree Crown Extraction,
ACIVS07(200-211).
Springer DOI Link 0708
BibRef

Horváth, P.[Peter], Jermyn, I.H.[Ian H.],
A New Phase Field Model of a 'Gas of Circles' for Tree Crown Extraction from Aerial Images,
CAIP07(702-709).
Springer DOI Link 0708
BibRef

Perrin, G.[Guillaume], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
2D and 3D Vegetation Resource Parameters Assessment using Marked Point Processes,
ICPR06(I: 1-4).
IEEE DOI Link 0609
BibRef
And:
A Non-Bayesian Model for Tree Crown Extraction using Marked Point Processes,
INRIARR-5846, 2006.
HTML Version. BibRef
Earlier:
A Marked Point Process Model for Tree Crown Extraction in Plantations,
ICIP05(I: 661-664).
IEEE DOI Link 0512
BibRef
Earlier:
Point processes in forestry: an application to tree crown detection,
INRIARR-5544, 2005.
HTML Version. BibRef

Descombes, X.[Xavier], Minlos, R.[Robert], Zhizhina, E.[Elena],
Object Extraction Using a Stochastic Birth-and-Death Dynamics in Continuum,
JMIV(33), No. 3, March 2009, pp. xx-yy.
Springer DOI Link 0903
Tree crown extraction. BibRef

Arslan, F.[Fatih], Descombes, X.[Xavier], Zerubia, J.B.[Josiane B.],
Object extraction from high resolution SAR images using a birth and death dynamics,
ICIP09(561-564).
IEEE DOI Link 0911
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 Link
WWW Version. 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 Link 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 Link 0805
BibRef

de Chant, T.[Tim], Kelly, M.[Maggi],
Individual Object Change Detection for Monitoring the Impact of a Forest Pathogen on a Hardwood Forest,
PhEngRS(75), No. 8, August 2009, pp. 1005-1014.
WWW Version. 0910
A novel change detection technique for tracking changes in individual forest canopy gaps over multiple years of imagery. BibRef

Daliakopoulos, I.N.[Ioannis N.], Grillakis, E.G.[Emmanouil G.], Koutroulis, A.G.[Aristeidis G.], Tsanis, I.K.[Ioannis K.],
Tree Crown Detection on Multispectral VHR Satellite Imagery,
PhEngRS(75), No. 10, October 2009, pp. 1201-1212.
WWW Version. 0910
A new method called Arbor Crown Enumerator was developed for tree crown detection from multispectral Very High Resolution satellite imagery. 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 Link
WWW Version. 1001
BibRef
Earlier:
3D Segmentation of Full Waveform LIDAR Data for Single Tree Detection Using Normalized Cut,
ISPRS08(B3a: 77 ff).
PDF Version. 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 Link 1110
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 Version. 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 Version. 0709
BibRef
Earlier:
Analysis of Full Waveform Lidar Data for Tree Species Classification,
PCV06(xx-yy).
PDF Version. 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 Link
WWW Version. 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 Link 1001
BibRef

Ceylan, N.[Nihal], Unal, E.[Ediz], Masson, J.[Josiane],
A Case Study of Developing An Olive Tree Database For Turkey,
PhEngRS(75), No. 12, December 2009, pp. 1397-1406.
WWW Version. 1001
An implementation of OLICOUNT software for counting olive trees over satellite imagery to test its practicability and to develop an olive database in Burhaniye County, Balkesir, Turkey. 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 Link 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 Link 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 Link 1003
BibRef

Hosoi, F.[Fumiki], Nakai, Y.[Yohei], Omasa, K.[Kenji],
Estimation and Error Analysis of Woody Canopy Leaf Area Density Profiles Using 3-D Airborne and Ground-Based Scanning Lidar Remote-Sensing Techniques,
GeoRS(48), No. 5, May 2010, pp. 2215-2223.
IEEE DOI Link 1006
BibRef
Earlier: A2, A1, A3:
Estimating Carbon Stocks of Coniferous, Woody Canopy Trees Using Airborne Lidar and Passive Optical Sensor,
Laser09(289). 0909
BibRef

Cho, M.A., Debba, P., Mathieu, R., Naidoo, L., van Aardt, J., Asner, G.P.,
Improving Discrimination of Savanna Tree Species Through a Multiple-Endmember Spectral Angle Mapper Approach: Canopy-Level Analysis,
GeoRS(48), No. 11, November 2010, pp. 4133-4142.
IEEE DOI Link 1011
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 Link
WWW Version. 1101
Laser scanning; Mobile; Unmanned aerial vehicle; Multi-sensor; Multitemporal BibRef

Lovell, J.L., Jupp, D.L.B., Newnham, G.J., Culvenor, D.S.,
Measuring tree stem diameters using intensity profiles from ground-based scanning lidar from a fixed viewpoint,
PandRS(66), No. 1, January 2011, pp. 46-55.
Elsevier DOI Link
WWW Version. 1101
LIDAR; Forestry; Inventory; Laser scanning; Terrestrial BibRef

Lopez, J.A.[J. Amoros], Verdiguier, E.I.[E. Izquierdo], Chova, L.G.[L. Gomez], Mari, J.M.[J. Munoz], Barreiro, J.Z.R.[J.Z. Rodriguez], Valls, G.C.[G. Camps], Maravilla, J.C.[J. Calpe],
Land cover classification of VHR airborne images for citrus grove identification,
PandRS(66), No. 1, January 2011, pp. 115-123.
Elsevier DOI Link
WWW Version. 1101
Tree identification; Feature extraction/selection; Classification tree; Support vector machine; Artificial neural networks 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 Link
WWW Version. 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 Link 1108
BibRef

Reis, S.[Selçuk], Tasdemir, K.[Kadim],
Identification of hazelnut fields using spectral and Gabor textural features,
PandRS(66), No. 5, September 2011, pp. 652-661.
Elsevier DOI Link
WWW Version. 1110
Orchard detection; Hazel orchards; Texture analysis; Multi-scale Gabor features; Self-organizing maps; Maximum likelihood classifier BibRef

Maselli, F.[Fabio], Chiesi, M.[Marta], Montaghi, A.[Alessandro], Pranzini, E.[Enzo],
Use of ETM+ images to extend stem volume estimates obtained from LiDAR data,
PandRS(66), No. 5, September 2011, pp. 662-671.
Elsevier DOI Link
WWW Version. 1110
Stem volume; LiDAR; Landsat ETM+; k-NN; Local regression BibRef

Ardila, J.P.[Juan P.], Tolpekin, V.A.[Valentyn A.], Bijker, W.[Wietske], Stein, A.[Alfred],
Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images,
PandRS(66), No. 6, November 2011, pp. 762-775.
Elsevier DOI Link
WWW Version. 1112
Image classification; Markov random field; Super resolution mapping; Urban trees; Contextual classification BibRef

Liang, X., Litkey, P., Hyyppa, J., Kaartinen, H., Vastaranta, M., Holopainen, M.,
Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning,
GeoRS(50), No. 2, February 2012, pp. 661-670.
IEEE DOI Link 1201
BibRef

Xu, J.[Jie], Qi, D.[Dawei],
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Holopainen, M.[Markus], Vastaranta, M.[Mikko], Kankare, V.[Ville], Räty, M.[Minna], Vaaja, M.[Matti], Liang, X.[Xinlian], Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Hyyppä, H.[Hannu], Viitala, R.[Risto], Kaasalainen, S.[Sanna],
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Raumonen, P.[Pasi], Kaasalainen, S.[Sanna], Kaasalainen, M.[Mikko], Kaartinen, H.[Harri],
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Schilling, A.[Anita], Schmidt, A.[Anja], Maas, H.G.[Hans-Gerd], Wagner, S.[Sven],
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Kankare, V.[Ville], Vastaranta, M.[Mikko], Holopainen, M.[Markus], Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Hyyppä, H.[Hannu],
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Korpela, I.S., Hovi, A., Morsdorf, F.,
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Canale, S., de Santis, A., Iacoviello, D., Pirri, F., Sagratella, S.,
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Chmielewski, L.J.[Leszek J.], Bator, M.[Marcin], Zasada, M.[Michal], Sterenczak, K.[Krzysztof], Strzelinski, P.[Pawel],
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Whiteside, T.[Tim], Taplin, P.[Pascale],
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Delaplace, K.L.W., van Coillie, F.M.B., de Wulf, R.R., Gabriels, D., de Smet, K., Ouessar, M., Belgacem, A.O.[A. Ouled], Houcine, T.,
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Kramer, H., Oldengarm, J.,
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Rafieyan, O., Darvishsefat, A.A., Babaii, S., Mataji, A.,
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van der Sande, C.J.,
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Ardila, J.P.[Juan Pablo], Tolpekin, V.A.[Valentyn A.], Bijker, W.[Wietske],
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Tolpekin, V.A.[Valentyn A.], Ardila, J.P.[Juan Pablo], Bijker, W.[Wietske],
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Bijker, W.[Wietske], Ardila, J.P.[Juan Pablo], Tolpekin, V.A.[Valentyn A.],
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Zhang, J.[Junjie], Sohn, G.[Gunho],
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Li, Z.R.[Zheng-Rong], Hayward, R.[Ross], Zhang, J.L.[Jing-Lan], Liu, Y.[Yuee], Walker, R.[Rodney],
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Petri, S., Immerkaer, J.,
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Li, Z.R.[Zheng-Rong], Hayward, R., Zhang, J.L.[Jing-Lan], Liu, Y.[Yuee],
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Guo, J.[Jun], Niu, Z.[Zheng],
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Riyahi, R., Kleinn, C., Fuchs, H.,
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Korpela, I., Tokola, T., Ørka, H.O., Koskinen, M.,
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Korpela, I., Dahlin, B., Schäfer, H., Bruun, E., Haapaniemi, F., Honkasalo, J., Ilvesniemi, S., Kuutti, V., Linkosalmi, M., Mustonen, J., Salo, M., Suomi, O., Virtanen, H.,
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Korpela, I.[Ilkka],
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Abd Rahman, M.Z.[Muhammad Zulkarnain], Gorte, B.G.H.[Ben G.H.],
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Abd Rahman, M.Z.[Muhammad Zulkarnain], Gorte, B.G.H.[Ben G.H.], Bucksch, A.[Alexander],
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Hyyppä, J., Mielonen, T., Hyyppä, H., Maltamo, M., Yu, X., Honkavaara, E., Kaartinen, H.,
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González, J., Galindo, C., Arevalo, V., Ambrosio, G.,
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Secord, J., Zakhor, A.,
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ICIP06(2317-2320).
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Radoux, J., Defourny, P.,
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Stach, N., Barnerias, C., Dommanget, A.,
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Chapter on Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR continues in
Forest Extraction, Forest Analysis .