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
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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.
IEEE DOI
1407
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.
IEEE DOI
1509
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],
Gaparovic, 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
BibRef
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
BibRef
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
BibRef
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.
IEEE DOI
1908
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
BibRef
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
BibRef
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.
IEEE DOI
1911
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
BibRef
Earlier:
Erratum:
RS(12), No. 19, 2020, pp. xx-yy.
DOI Link
2010
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
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
BibRef
Salekin, S.[Serajis],
Pont, D.[David],
Dickinson, Y.[Yvette],
Amarasena, S.[Sumedha],
Spatially Explicit Individual Tree Height Growth Models from
Bi-Temporal Aerial Laser Scanning,
RS(16), No. 13, 2024, pp. 2270.
DOI Link
2407
BibRef
Király, G.,
Brolly, G.,
Tree Height Estimation Methods for Terrestrial Laser Scanning in a
Forest Reserve,
Laser07(211).
PDF File.
0709
BibRef
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,
Laser07(401).
PDF File.
0709
BibRef
Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Biomass Measurements, Forest, LiDAR Techniques, Airborne Laser .