Tree Height Measurement

Chapter Contents (Back)
Height. Tree Height. Somewhat related:
See also Canopy Height Measurement. Diameter:
See also Tree Diameter, Tree Width, Stem Diameter, Diameter at Breast Height, DBH.
See also Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS.

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

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 Link. 0304

Santoro, M., Askne, J., Dammert, P.B.G.,
Tree height influence on ERS interferometric phase in boreal forest,
GeoRS(43), No. 2, February 2005, pp. 207-217.
IEEE Abstract. 0501

Shi, Y.[Yuli], Choi, S.H.[Sung-Ho], Ni, X.L.[Xi-Liang], Ganguly, S., Zhang, G., Duong, H., Lefsky, M.A.[Michael A.], Simard, M.[Marc], Saatchi, S., Lee, S., Ni-Meister, W., Piao, S., Cao, C.X.[Chun-Xiang], Nemani, R., Myneni, R.B.[Ranga B.],
Allometric Scaling and Resource Limitations Model of Tree Heights: Part 1. Model Optimization and Testing over Continental USA,
RS(5), No. 1, January 2013, pp. 284-306.
DOI Link 1302

Choi, S.H.[Sung-Ho], Ni, X.L.[Xi-Liang], Shi, Y.[Yuli], Ganguly, S., Zhang, G., Duong, H., Lefsky, M.A.[Michael A.], Simard, M.[Marc], Saatchi, S., Lee, S., Ni-Meister, W., Piao, S., Cao, C.X.[Chun-Xiang], Nemani, R., Myneni, R.B.[Ranga B.],
Allometric Scaling and Resource Limitations Model of Tree Heights: Part 2. Site Based Testing of the Model,
RS(5), No. 1, January 2013, pp. 202-223.
DOI Link 1302

Ni, X.L.[Xi-Liang], Park, T.J.[Tae-Jin], Choi, S.H.[Sung-Ho], Shi, Y.[Yuli], Cao, C.X.[Chun-Xiang], Wang, X.J.[Xue-Jun], Lefsky, M.A.[Michael A.], Simard, M.[Marc], Myneni, R.B.[Ranga B.],
Allometric Scaling and Resource Limitations Model of Tree Heights: Part 3. Model Optimization and Testing over Continental China,
RS(6), No. 5, 2014, pp. 3533-3553.
DOI Link 1407

Kugler, F., Schulze, D., Hajnsek, I., Pretzsch, H., Papathanassiou, K.P.,
TanDEM-X Pol-InSAR Performance for Forest Height Estimation,
GeoRS(52), No. 10, October 2014, pp. 6404-6422.
Coherence BibRef

Kugler, F., Lee, S.K.[Seung-Kuk], Hajnsek, I., Papathanassiou, K.P.,
Forest Height Estimation by Means of Pol-InSAR Data Inversion: The Role of the Vertical Wavenumber,
GeoRS(53), No. 10, October 2015, pp. 5294-5311.
airborne radar BibRef

Wang, Y.S.[Yun-Sheng], Lehtomäki, M.[Matti], Liang, X.L.[Xin-Lian], Pyörälä, J.[Jiri], Kukko, A.[Antero], Jaakkola, A.[Anttoni], Liu, J.B.[Jing-Bin], Feng, Z.Y.[Zi-Yi], Chen, R.Z.[Rui-Zhi], Hyyppä, J.[Juha],
Is field-measured tree height as reliable as believed: A comparison study of tree height estimates from field measurement, airborne laser scanning and terrestrial laser scanning in a boreal forest,
PandRS(147), 2019, pp. 132-145.
Elsevier DOI 1901
Tree height, Field measurement, Airborne laser scanning, Terrestrial laser scanning, Accuracy, Individual tree, Forest inventory BibRef

Jurjevic, L.[Luka], Liang, X.L.[Xin-Lian], Gašparovic, M.[Mateo], Balenovic, I.[Ivan],
Is field-measured tree height as reliable as believed: Part II, A comparison study of tree height estimates from conventional field measurement and low-cost close-range remote sensing in a deciduous forest,
PandRS(169), 2020, pp. 227-241.
Elsevier DOI 2011
Tree height, Close-range remote sensing, Field measurement, Unmanned-borne laser scanning, Photogrammetry, Hand-held personal laser scanning BibRef

Krause, S.[Stuart], Sanders, T.G.M.[Tanja G.M.], Mund, J.P.[Jan-Peter], Greve, K.[Klaus],
UAV-Based Photogrammetric Tree Height Measurement for Intensive Forest Monitoring,
RS(11), No. 7, 2019, pp. xx-yy.
DOI Link 1904

Bollandsås, O.M.[Ole Martin], Ørka, H.O.[Hans Ole], Dalponte, M.[Michele], Gobakken, T.[Terje], Næsset, E.[Erik],
Modelling Site Index in Forest Stands Using Airborne Hyperspectral Imagery and Bi-Temporal Laser Scanner Data,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
Site index is most commonly expressed as the average height of the dominant trees at a certain index age. BibRef

Ni, W.J.[Wen-Jian], Zhang, Z.Y.[Zhi-Yu], Sun, G.Q.[Guo-Qing], Liu, Q.H.[Qin-Huo],
Modeling the Stereoscopic Features of Mountainous Forest Landscapes for the Extraction of Forest Heights from Stereo Imagery,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906

He, H.Q.[Hai-Qing], Yan, Y.[Yeli], Chen, T.[Ting], Cheng, P.G.[Peng-Gen],
Tree Height Estimation of Forest Plantation in Mountainous Terrain from Bare-Earth Points Using a DoG-Coupled Radial Basis Function Neural Network,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906

Wang, X., Xu, F.,
A PolinSAR Inversion Error Model on Polarimetric System Parameters for Forest Height Mapping,
GeoRS(57), No. 8, August 2019, pp. 5669-5685.
forestry, radar imaging, radar interferometry, radar polarimetry, remote sensing by radar, synthetic aperture radar, polarimetric system requirement BibRef

Huang, H.B.[Hua-Bing], Liu, C.X.[Cai-Xia], Wang, X.Y.[Xiao-Yi],
Constructing a Finer-Resolution Forest Height in China Using ICESat/GLAS, Landsat and ALOS PALSAR Data and Height Patterns of Natural Forests and Plantations,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908

Næsset, E.[Erik], Gobakken, T.[Terje], McRoberts, R.E.[Ronald E.],
A Model-Dependent Method for Monitoring Subtle Changes in Vegetation Height in the Boreal-Alpine Ecotone Using Bi-Temporal, Three Dimensional Point Data from Airborne Laser Scanning,
RS(11), No. 15, 2019, pp. xx-yy.
DOI Link 1908

Liao, Z., He, B., Bai, X., Quan, X.,
Improving Forest Height Retrieval by Reducing the Ambiguity of Volume-Only Coherence Using Multi-Baseline PolInSAR Data,
GeoRS(57), No. 11, November 2019, pp. 8853-8866.
Forestry, Decorrelation, Coherence, Laser radar, Synthetic aperture radar, Biomass, Solid modeling, Forest height, volume-only coherence BibRef

Stefanidou, A.[Alexandra], Gitas, I.Z.[Ioannis Z.], Korhonen, L.[Lauri], Stavrakoudis, D.[Dimitris], Georgopoulos, N.[Nikos],
LiDAR-Based Estimates of Canopy Base Height for a Dense Uneven-Aged Structured Forest,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
Earlier: Erratum: RS(12), No. 19, 2020, pp. xx-yy.
DOI Link 2010

Healey, S.P.[Sean P.], Yang, Z.Q.[Zhi-Qiang], Gorelick, N.[Noel], Ilyushchenko, S.[Simon],
Highly Local Model Calibration with a New GEDI LiDAR Asset on Google Earth Engine Reduces Landsat Forest Height Signal Saturation,
RS(12), No. 17, 2020, pp. xx-yy.
DOI Link 2009

Chadwick, A.J.[Andrew J.], Goodbody, T.R.H.[Tristan R. H.], Coops, N.C.[Nicholas C.], Hervieux, A.[Anne], Bater, C.W.[Christopher W.], Martens, L.A.[Lee A.], White, B.[Barry], Röeser, D.[Dominik],
Automatic Delineation and Height Measurement of Regenerating Conifer Crowns under Leaf-Off Conditions Using UAV Imagery,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012

Kameyama, S.[Shohei], Sugiura, K.[Katsuaki],
Effects of Differences in Structure from Motion Software on Image Processing of Unmanned Aerial Vehicle Photography and Estimation of Crown Area and Tree Height in Forests,
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103

Ramachandran, N.[Naveen], Saatchi, S.[Sassan], Tebaldini, S.[Stefano], d'Alessandro, M.M.[Mauro Mariotti], Dikshit, O.[Onkar],
Evaluation of P-Band SAR Tomography for Mapping Tropical Forest Vertical Backscatter and Tree Height,
RS(13), No. 8, 2021, pp. xx-yy.
DOI Link 2104

Liu, X.[Xin], Hao, Y.S.[Yuan-Shuo], Widagdo, F.R.A.[Faris Rafi Almay], Xie, L.F.[Long-Fei], Dong, L.[Lihu], Li, F.R.[Feng-Ri],
Predicting Height to Crown Base of Larix olgensis in Northeast China Using UAV-LiDAR Data and Nonlinear Mixed Effects Models,
RS(13), No. 9, 2021, pp. xx-yy.
DOI Link 2105

Kobal, M.[Milan], Hladnik, D.[David],
Tree Height Growth Modelling Using LiDAR-Derived Topography Information,
IJGI(10), No. 6, 2021, pp. xx-yy.
DOI Link 2106

Næsset, E.[Erik], Gobakken, T.[Terje], Jutras-Perreault, M.C.[Marie-Claude], Ramtvedt, E.N.[Eirik Næsset],
Comparing 3D Point Cloud Data from Laser Scanning and Digital Aerial Photogrammetry for Height Estimation of Small Trees and Other Vegetation in a Boreal-Alpine Ecotone,
RS(13), No. 13, 2021, pp. xx-yy.
DOI Link 2107

Soja, M.J.[Maciej J.], Karlson, M.[Martin], Bayala, J.[Jules], Bazié, H.R.[Hugues R.], Sanou, J.[Josias], Tankoano, B.[Boalidioa], Eriksson, L.E.B.[Leif E. B.], Reese, H.[Heather], Ostwald, M.[Madelene], Ulander, L.M.H.[Lars M. H.],
Mapping Tree Height in Burkina Faso Parklands with TanDEM-X,
RS(13), No. 14, 2021, pp. xx-yy.
DOI Link 2107

Hao, Z.B.[Zhen-Bang], Lin, L.[Lili], Post, C.J.[Christopher J.], Mikhailova, E.A.[Elena A.], Li, M.H.[Ming-Hui], Chen, Y.[Yan], Yu, K.[Kunyong], Liu, J.[Jian],
Automated tree-crown and height detection in a young forest plantation using mask region-based convolutional neural network (Mask R-CNN),
PandRS(178), 2021, pp. 112-123.
Elsevier DOI 2108
Deep learning, Instance segmentation, Tree-crown delineation, Tree height, UAV imagery, Plantation forest BibRef

Kozniewski, M.[Marcin], Kolendo, L.[Lukasz], Ksepko, M.[Marek], Chmur, S.[Szymon],
Tracking Individual Scots Pine (Pinus sylvestris L.) Height Growth Using Multi-Temporal ALS Data from North-Eastern Poland,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209

Xuan, J.[Jie], Li, X.J.[Xue-Jian], Du, H.Q.[Hua-Qiang], Zhou, G.[Guomo], Mao, F.J.[Fang-Jie], Wang, J.Y.[Jing-Yi], Zhang, B.[Bo], Gong, Y.L.[Yu-Lin], Zhu, D.[Di'en], Zhou, L.[Lv], Huang, Z.[Zihao], Xu, C.[Cenheng], Chen, J.J.[Jin-Jin], Zhou, Y.X.[Yong-Xia], Chen, C.[Chao], Tan, C.[Cheng], Sun, J.Q.[Jia-Qian],
Intelligent Estimating the Tree Height in Urban Forests Based on Deep Learning Combined with a Smartphone and a Comparison with UAV-LiDAR,
RS(15), No. 1, 2023, pp. xx-yy.
DOI Link 2301

Tang, X.[Xu], You, H.T.[Hao-Tian], Liu, Y.[Yao], You, Q.[Qixu], Chen, J.J.[Jian-Jun],
Monitoring of Monthly Height Growth of Individual Trees in a Subtropical Mixed Plantation Using UAV Data,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301

Liu, C.[Chang], Zhang, Q.[Qi], Ge, L.L.[Lin-Lin], Sepasgozar, S.M.E.[Samad M. E.], Sheng, Z.H.[Zi-Heng],
Dielectric Fluctuation and Random Motion over Ground Model (DF-RMoG): An Unsupervised Three-Stage Method of Forest Height Estimation Considering Dielectric Property Changes,
RS(15), No. 7, 2023, pp. 1877.
DOI Link 2304

Song, H.[Hao], Zhou, H.[Hui], Wang, H.[Heng], Ma, Y.[Yue], Zhang, Q.Y.[Qian-Yin], Li, S.[Song],
Retrieval of Tree Height Percentiles over Rugged Mountain Areas via Target Response Waveform of Satellite Lidar,
RS(16), No. 2, 2024, pp. 425.
DOI Link 2402

Fang, R.,
Impacts Of Tree Height-DBH Allometry On Lidar-based Tree Aboveground Biomass Modeling,
ISPRS16(B8: 625-628).
DOI Link 1610

Király, G., Brolly, G.,
Tree Height Estimation Methods for Terrestrial Laser Scanning in a Forest Reserve,
PDF File. 0709

Takahashi, T., Awaya, Y., Hirata, Y., Furuya, N., Sakai, T., Sakai, A.,
Assessment of LiDAR-Derived Tree Heights Estimated from Different Flight Altitude Data in Mountainous Forests with Poor Laser Penetration Rates,
PDF File. 0709

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Biomass Measurements, Forest, LiDAR Techniques, Airborne Laser .

Last update:May 6, 2024 at 15:50:14