Trees, Forest Canopy Analysis

Chapter Contents (Back)
Forest Canopy. Forest. Trees. Canopy.
See also Canopy Water Content.
See also Trees, Individual Trees.
See also Trees, Forest, Stem Volume, Aboveground Biomass Measurements.
See also Clumping Index, Measurement, Effects.

Li, X., and Strahler, A.H.,
Geometric-optical modeling of a conifer forest canopy,
GeoRS(23), No. 5, September 1985, pp. 705-720. BibRef 8509

Li, X., and Strahler, A.H.,
Geometric-optical bidirectional reflectance modeling of the discrete crown vegetation canopy: Effect of crown shape and mutual shadowing,
GeoRS(30), No. 3, March 1992, pp. 276-292. BibRef 9203

Sheng, Y.W.[Yong-Wei], Gong, P.[Peng], Biging, G.S.[Gregory S.],
Model-Based Conifer Canopy Surface Reconstruction from Photographic Imagery: Overcoming the Occlusion, Foreshortening, and Edge Effects,
PhEngRS(69), No. 3, March 2003, pp. 249-258. The capability of the model-based surface reconstruction approach is extended from recovering the crown surface of a single tree to reconstructing the canopy surface of a tree stand, and is further developed to canopy surface reconstruction for complicated tree stands.
WWW Link. 0304

Sheng, Y.W.[Yong-Wei], Gong, P.[Peng], Biging, G.S.[Gregory S.],
True Orthoimage Production for Forested Areas from Large-Scale Aerial Photographs,
PhEngRS(69), No. 3, March 2003, pp. 259-266. An effort for removing occlusion and correcting canopy relief displacement using a canopy surface model (CSM) in true orthoimage generation for forested areas is described.
WWW Link. 0304

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.

Xu, F., Jin, Y.Q.,
Multiparameter Inversion of a Layer of Vegetation Canopy Over Rough Surface From the System Response Function Based on the Mueller Matrix Solution of Pulse Echoes,
GeoRS(44), No. 7, Part 2, July 2006, pp. 2003-2015.

Verhoef, W., Jia, L., Xiao, Q., Su, Z.,
Unified Optical-Thermal Four-Stream Radiative Transfer Theory for Homogeneous Vegetation Canopies,
GeoRS(45), No. 6, June 2007, pp. 1808-1822.

Yang, P.Q.[Pei-Qi], Verhoef, W.[Wout], van der Tol, C.[Christiaan],
Unified Four-Stream Radiative Transfer Theory in the Optical-Thermal Domain with Consideration of Fluorescence for Multi-Layer Vegetation Canopies,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012

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 Link. 0910
A novel change detection technique for tracking changes in individual forest canopy gaps over multiple years of imagery. BibRef

Liu, D., Sun, G., Guo, Z., Ranson, K.J., Du, Y.,
Three-Dimensional Coherent Radar Backscatter Model and Simulations of Scattering Phase Center of Forest Canopies,
GeoRS(48), No. 1, January 2010, pp. 349-357.

Neumann, M., Ferro-Famil, L., Reigber, A.,
Estimation of Forest Structure, Ground, and Canopy Layer Characteristics From Multibaseline Polarimetric Interferometric SAR Data,
GeoRS(48), No. 3, March 2010, pp. 1086-1104.

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.
Earlier: A2, A1, A3:
Estimating Carbon Stocks of Coniferous, Woody Canopy Trees Using Airborne Lidar and Passive Optical Sensor,
Laser09(289). 0909

Dorigo, W., Richter, R., Baret, F., Bamler, R., Wagner, W.,
Enhanced Automated Canopy Characterization from Hyperspectral Data by a Novel Two Step Radiative Transfer Model Inversion Approach,
RS(1), No. 4, December 2009, pp. 1139-1170.
DOI Link 1203

Wang, J., Lang, P.,
Detection of Cypress Canopies in the Florida Panhandle Using Subpixel Analysis and GIS,
RS(1), No. 4, December 2009, pp. 1028-1042.
DOI Link 1203

Peña, M.A.[Marco A.], Brenning, A.[Alexander], Sagredo, A.[Ariel],
Constructing satellite-derived hyperspectral indices sensitive to canopy structure variables of a Cordilleran Cypress (Austrocedrus chilensis) forest,
PandRS(74), No. 1, November 2012, pp. 1-10.
Elsevier DOI 1212
Hyperspectral imaging; Spectral indices; Austrocedrus chilensis; Forest canopy structure; False discovery rate; Multiple comparison problem BibRef

Gong, W.[Wei], Song, S.L.[Sha-Lei], Zhu, B.[Bo], Shi, S.[Shuo], Li, F.Q.[Fa-Quan], Cheng, X.W.[Xue-Wu],
Multi-wavelength canopy LiDAR for remote sensing of vegetation: Design and system performance,
PandRS(69), No. 1, April 2012, pp. 1-9.
Elsevier DOI 1202
Multi-wavelength canopy LiDAR; Remote sensing; Vegetation physiology; Wavelength selection; Laser vegetation index BibRef

Tabatabaeenejad, A., Burgin, M., Moghaddam, M.,
Potential of L-Band Radar for Retrieval of Canopy and Subcanopy Parameters of Boreal Forests,
GeoRS(50), No. 6, June 2012, pp. 2150-2160.

Sharma, R.C.[Ram C.], Kajiwara, K.[Koji], Honda, Y.[Yoshiaki],
Estimation of forest canopy structural parameters using kernel-driven bi-directional reflectance model based multi-angular vegetation indices,
PandRS(78), No. 1, April 2013, pp. 50-57.
Elsevier DOI 1304
Forest canopy; Canopy 3D structure; Near-surface bi-directional reflectance; Multi-angular vegetation indices; BRDF parameters; Canopy structural index BibRef

Zhao, F.[Feng], Guo, Y.Q.[Yi-Qing], Verhoef, W.[Wout], Gu, X.F.[Xing-Fa], Liu, L.Y.[Liang-Yun], Yang, G.J.[Gui-Jun],
A Method to Reconstruct the Solar-Induced Canopy Fluorescence Spectrum from Hyperspectral Measurements,
RS(6), No. 10, 2014, pp. 10171-10192.
DOI Link 1411

Hightower, J.N.[Jessica N.], Butterfield, A.C.[A. Christine], Weishampel, J.F.[John F.],
Quantifying Ancient Maya Land Use Legacy Effects on Contemporary Rainforest Canopy Structure,
RS(6), No. 11, 2014, pp. 10716-10732.
DOI Link 1412

Hernandez-Clemente, R., Navarro-Cerrillo, R.M., Zarco-Tejada, P.J.,
Deriving Predictive Relationships of Carotenoid Content at the Canopy Level in a Conifer Forest Using Hyperspectral Imagery and Model Simulation,
GeoRS(52), No. 8, August 2014, pp. 5206-5217.
Hyperspectral imaging BibRef

Asner, G.P.[Gregory P.], Martin, R.E.[Roberta E.],
Spectroscopic Remote Sensing of Non-Structural Carbohydrates in Forest Canopies,
RS(7), No. 4, 2015, pp. 3526-3547.
DOI Link 1505

Li, C.R.[Cong-Rong], Song, J.L.[Jin-Ling], Wang, J.[Jindi],
Modifying Geometric-Optical Bidirectional Reflectance Model for Direct Inversion of Forest Canopy Leaf Area Index,
RS(7), No. 9, 2015, pp. 11083.
DOI Link 1511

Hansen, E.H.[Endre Hofstad], Gobakken, T.[Terje], Næsset, E.[Erik],
Effects of Pulse Density on Digital Terrain Models and Canopy Metrics Using Airborne Laser Scanning in a Tropical Rainforest,
RS(7), No. 7, 2015, pp. 8453.
DOI Link 1506

Ferraz, A., Mallet, C., Jacquemoud, S., Rito Goncalves, G., Tome, M., Soares, P., Gomes Pereira, L., Bretar, F.,
Canopy Density Model: A New ALS-Derived Product to Generate Multilayer Crown Cover Maps,
GeoRS(53), No. 12, December 2015, pp. 6776-6790.
geophysical techniques BibRef

Song, Y., Imanishi, J., Hashimoto, H., Morimura, A., Morimoto, Y., Kitada, K.,
Spectral Correction for the Effect of Crown Shape at the Single-Tree Level: An Approach Using a Lidar-Derived Digital Surface Model for Broad-Leaved Canopy,
GeoRS(51), No. 2, February 2013, pp. 755-764.

Moreno, A.[April], Tangenberg, J.[John], Hilton, B.N.[Brian N.], Hilton, J.K.[June K.],
An Environmental Assessment of School Shade Tree Canopy and Implications for Sun Safety Policies: The Los Angeles Unified School District,
IJGI(4), No. 2, 2015, pp. 607-625.
DOI Link 1505

Pimont, F.[François], Dupuy, J.L.[Jean-Luc], Rigolot, E.[Eric], Prat, V.[Vincent], Piboule, A.[Alexandre],
Estimating Leaf Bulk Density Distribution in a Tree Canopy Using Terrestrial LiDAR and a Straightforward Calibration Procedure,
RS(7), No. 6, 2015, pp. 7995.
DOI Link 1507
And: Correction: RS(8), No. 1, 2016, pp. 64.
DOI Link 1602

McManus, K.M.[Kelly M.], Asner, G.P.[Gregory P.], Martin, R.E.[Roberta E.], Dexter, K.G.[Kyle G.], Kress, W.J.[W. John], Field, C.B.[Christopher B.],
Phylogenetic Structure of Foliar Spectral Traits in Tropical Forest Canopies,
RS(8), No. 3, 2016, pp. 196.
DOI Link 1604

Wang, Z.H.[Zhi-Hui], Wang, T.J.[Tie-Jun], Darvishzadeh, R.[Roshanak], Skidmore, A.K.[Andrew K.], Jones, S.[Simon], Suarez, L.[Lola], Woodgate, W.[William], Heiden, U.[Uta], Heurich, M.[Marco], Hearne, J.[John],
Vegetation Indices for Mapping Canopy Foliar Nitrogen in a Mixed Temperate Forest,
RS(8), No. 6, 2016, pp. 491.
DOI Link 1608

Ali, A.M.[Abebe Mohammed], Skidmore, A.K.[Andrew K.], Darvishzadeh, R.[Roshanak], van Duren, I.[Iris], Holzwarth, S.[Stefanie], Mueller, J.[Joerg],
Retrieval of forest leaf functional traits from HySpex imagery using radiative transfer models and continuous wavelet analysis,
PandRS(122), No. 1, 2016, pp. 68-80.
Elsevier DOI 1612
Continuous wavelet analysis BibRef

Mahoney, C.[Craig], Hopkinson, C.[Chris], Kljun, N.[Natascha], van Gorsel, E.[Eva],
Estimating Canopy Gap Fraction Using ICESat GLAS within Australian Forest Ecosystems,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702

Dutta, D., Wang, K., Lee, E., Goodwell, A., Woo, D.K., Wagner, D., Kumar, P.,
Characterizing Vegetation Canopy Structure Using Airborne Remote Sensing Data,
GeoRS(55), No. 2, February 2017, pp. 1160-1178.
forestry BibRef

Hardiman, B.S.[Brady S.], Gough, C.M.[Christopher M.], Butnor, J.R.[John R.], Bohrer, G.[Gil], Detto, M.[Matteo], Curtis, P.S.[Peter S.],
Coupling Fine-Scale Root and Canopy Structure Using Ground-Based Remote Sensing,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703

Perroy, R.L.[Ryan L.], Sullivan, T.[Timo], Stephenson, N.[Nathan],
Assessing the impacts of canopy openness and flight parameters on detecting a sub-canopy tropical invasive plant using a small unmanned aerial system,
PandRS(125), No. 1, 2017, pp. 174-183.
Elsevier DOI 1703
Miconia calvescens BibRef

Zhou, Y., Hilker, T., Ju, W., Coops, N.C., Black, T.A., Chen, J.M., Wu, X.,
Modeling Gross Primary Production for Sunlit and Shaded Canopies Across an Evergreen and a Deciduous Site in Canada,
GeoRS(55), No. 4, April 2017, pp. 1859-1873.
forestry BibRef

Bremer, M.[Magnus], Wichmann, V.[Volker], Rutzinger, M.[Martin],
Calibration and Validation of a Detailed Architectural Canopy Model Reconstruction for the Simulation of Synthetic Hemispherical Images and Airborne LiDAR Data,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704

Harikumar, A., Bovolo, F., Bruzzone, L.,
An Internal Crown Geometric Model for Conifer Species Classification With High-Density LiDAR Data,
GeoRS(55), No. 5, May 2017, pp. 2924-2940.
forestry, geophysical image processing, image classification, optical radar, remote sensing by laser beam, support vector machines, vegetation, Italy, Trentino region, conifer species classification, conifer tree, forest management practice, forest vertical profile, high-density LiDAR data, high-density small footprint multireturn airborne light detection and ranging scanning, internal branch structure model, internal crown geometric model, principal component analysis, support vector machine, tree external crown characteristics, tree species, Atmospheric modeling, Data models, Laser radar, Optical imaging, Optical sensors, Support vector machines, Vegetation, Airborne laser scanning, conifers, feature extraction, forestry, light detection and ranging (LiDAR), support vector machines (SVMs), tree, species BibRef

Milenkovic, M.[Milutin], Wagner, W.[Wolfgang], Quast, R.[Raphael], Hollaus, M.[Markus], Ressl, C.[Camillo], Pfeifer, N.[Norbert],
Total canopy transmittance estimated from small-footprint, full-waveform airborne LiDAR,
PandRS(128), No. 1, 2017, pp. 61-72.
Elsevier DOI 1706
Airborne, laser, scanning BibRef

Hamraz, H.[Hamid], Contreras, M.A.[Marco A.], Zhang, J.[Jun],
Vertical stratification of forest canopy for segmentation of understory trees within small-footprint airborne LiDAR point clouds,
PandRS(130), No. 1, 2017, pp. 385-392.
Elsevier DOI 1708
Remote, sensing BibRef

Yin, G., Li, A., Zhao, W., Jin, H., Bian, J., Wu, S.,
Modeling Canopy Reflectance Over Sloping Terrain Based on Path Length Correction,
GeoRS(55), No. 8, August 2017, pp. 4597-4609.
Biological system modeling, Computational modeling, Remote sensing, Scattering, Solid modeling, Surface topography, Vegetation mapping, Canopy reflectance (CR) modeling, path length correction (PLC), radiative transfer, remote sensing, topographic, effects BibRef

de Moura, Y.M.[Yhasmin Mendes], Soares Galvão, L.[Lênio], Hilker, T.[Thomas], Wu, J.[Jin], Saleska, S.[Scott], do Amaral, C.H.[Cibele Hummel], Nelson, B.W.[Bruce Walker], Lopes, A.P.[Aline Pontes], Wiedeman, K.K.[Kenia K.], Prohaska, N.[Neill], de Oliveira, R.C.[Raimundo Cosme], Machado, C.B.[Carolyne Bueno], Aragão, L.E.O.C.[Luiz E.O.C.],
Spectral analysis of amazon canopy phenology during the dry season using a tower hyperspectral camera and modis observations,
PandRS(131), No. 1, 2017, pp. 52-64.
Elsevier DOI 1709
Phenology BibRef

Shen, X.[Xin], Cao, L.[Lin],
Tree-Species Classification in Subtropical Forests Using Airborne Hyperspectral and LiDAR Data,
RS(9), No. 11, 2017, pp. xx-yy.
DOI Link 1712

Shen, X.[Xin], Cao, L.[Lin], Chen, D.[Dong], Sun, Y.[Yuan], Wang, G.[Guibin], Ruan, H.H.[Hong-Hua],
Prediction of Forest Structural Parameters Using Airborne Full-Waveform LiDAR and Hyperspectral Data in Subtropical Forests,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Zhang, Z.N.[Zheng-Nan], Cao, L.[Lin], She, G.H.[Guang-Hui],
Estimating Forest Structural Parameters Using Canopy Metrics Derived from Airborne LiDAR Data in Subtropical Forests,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711

Senécal, J.F.[Jean-Francois], Doyon, F.[Frédérik], Messier, C.[Christian],
Tree Death Not Resulting in Gap Creation: An Investigation of Canopy Dynamics of Northern Temperate Deciduous Forests,
RS(10), No. 1, 2018, pp. xx-yy.
DOI Link 1802

Wu, Q.L.[Qiao-Li], Song, C.H.[Cong-He], Song, J.L.[Jin-Ling], Wang, J.[Jindi], Chen, S.Y.[Shao-Yuan], Yu, B.[Bo],
Impacts of Leaf Age on Canopy Spectral Signature Variation in Evergreen Chinese Fir Forests,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804

Feng, Z., Chen, Y., Hyyppo, J., Hakala, T., Zhou, H., Wang, Y., Karjalainen, M.,
Estimating Ground Level and Canopy Top Elevation With Airborne Microwave Profiling Radar,
GeoRS(56), No. 4, April 2018, pp. 2283-2294.
Estimation, Laser radar, Microwave theory and techniques, Radar remote sensing, Spaceborne radar, Synthetic aperture radar, tree canopy top elevation BibRef

Gara, T.W.[Tawanda W.], Darvishzadeh, R.[Roshanak], Skidmore, A.K.[Andrew K.], Wang, T.J.[Tie-Jun],
Impact of Vertical Canopy Position on Leaf Spectral Properties and Traits across Multiple Species,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804

Ni, W., Zhang, Z., Sun, G., Liu, Q.,
Modeling Interferometric SAR Features of Forest Canopies Over Mountainous Area at Landscape Scales,
GeoRS(56), No. 5, May 2018, pp. 2958-2967.
Analytical models, Backscatter, Biological system modeling, Scattering, Solid modeling, Synthetic aperture radar, Vegetation, synthetic aperture radar (SAR) BibRef

Cuba, N.[Nicholas], Rogan, J.[John], Lawrence, D.[Deborah], Williams, C.[Christopher],
Cross-Scale Correlation between In Situ Measurements of Canopy Gap Fraction and Landsat-Derived Vegetation Indices with Implications for Monitoring the Seasonal Phenology in Tropical Forests Using MODIS Data,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808

Lin, C.S.[Chin-Su],
A Generalized Logistic-Gaussian-Complex Signal Model for the Restoration of Canopy SWIR Hyperspectral Reflectance,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
Short Wave IR BibRef

Shin, P.[Patrick], Sankey, T.[Temuulen], Moore, M.M.[Margaret M.], Thode, A.E.[Andrea E.],
Evaluating Unmanned Aerial Vehicle Images for Estimating Forest Canopy Fuels in a Ponderosa Pine Stand,
RS(10), No. 8, 2018, pp. xx-yy.
DOI Link 1809

Lin, S.R.[Shang-Rong], Li, J.[Jing], Liu, Q.H.[Qin-Huo], Huete, A.[Alfredo], Li, L.H.[Long-Hui],
Effects of Forest Canopy Vertical Stratification on the Estimation of Gross Primary Production by Remote Sensing,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Bagaram, M.B.[Martin B.], Giuliarelli, D.[Diego], Chirici, G.[Gherardo], Giannetti, F.[Francesca], Barbati, A.[Anna],
UAV Remote Sensing for Biodiversity Monitoring: Are Forest Canopy Gaps Good Covariates?,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810

Levashova, N.[Natalia], Lukyanenko, D.[Dmitry], Mukhartova, Y.[Yulia], Olchev, A.[Alexander],
Application of a Three-Dimensional Radiative Transfer Model to Retrieve the Species Composition of a Mixed Forest Stand from Canopy Reflected Radiation,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811

Cao, B., Guo, M., Fan, W., Xu, X., Peng, J., Ren, H., Du, Y., Li, H., Bian, Z., Hu, T., Xiao, Q., Liu, Q.,
A New Directional Canopy Emissivity Model Based on Spectral Invariants,
GeoRS(56), No. 12, December 2018, pp. 6911-6926.
Mathematical model, Photonics, Soil, Vegetation mapping, Probability, Absorption, Scattering, Canopy emissivity, land surface emissivity, spectral invariants BibRef

Wang, W.[Weile], Nemani, R.[Ramakrishna], Hashimoto, H.[Hirofumi], Ganguly, S.[Sangram], Huang, D.[Dong], Knyazikhin, Y.[Yuri], Myneni, R.[Ranga], Bala, G.[Govindasamy],
An Interplay between Photons, Canopy Structure, and Recollision Probability: A Review of the Spectral Invariants Theory of 3D Canopy Radiative Transfer Processes,
RS(10), No. 11, 2018, pp. xx-yy.
DOI Link 1812

Adams, J.[Jennifer], Lewis, P.[Philip], Disney, M.[Mathias],
Decoupling Canopy Structure and Leaf Biochemistry: Testing the Utility of Directional Area Scattering Factor (DASF),
RS(10), No. 12, 2018, pp. xx-yy.
DOI Link 1901

Wu, H.Y.[Hui-Ying], Levin, N.[Noam], Seabrook, L.[Leonie], Moore, B.D.[Ben D.], McAlpine, C.[Clive],
Mapping Foliar Nutrition Using WorldView-3 and WorldView-2 to Assess Koala Habitat Suitability,
RS(11), No. 3, 2019, pp. xx-yy.
DOI Link 1902

Huesca, M.[Margarita], Roth, K.L.[Keely L.], García, M.[Mariano], Ustin, S.L.[Susan L.],
Discrimination of Canopy Structural Types in the Sierra Nevada Mountains in Central California,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905

Xu, N.X.[Nian-Xu], Tian, J.[Jia], Tian, Q.J.[Qing-Jiu], Xu, K.J.[Kai-Jian], Tang, S.F.[Shao-Fei],
Analysis of Vegetation Red Edge with Different Illuminated/Shaded Canopy Proportions and to Construct Normalized Difference Canopy Shadow Index,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906

Hallik, L.[Lea], Kuusk, A.[Andres], Lang, M.[Mait], Kuusk, J.[Joel],
Reflectance Properties of Hemiboreal Mixed Forest Canopies with Focus on Red Edge and Near Infrared Spectral Regions,
RS(11), No. 14, 2019, pp. xx-yy.
DOI Link 1908

Cogliati, S.[Sergio], Celesti, M.[Marco], Cesana, I.[Ilaria], Miglietta, F.[Franco], Genesio, L.[Lorenzo], Julitta, T.[Tommaso], Schuettemeyer, D.[Dirk], Drusch, M.[Matthias], Rascher, U.[Uwe], Jurado, P.[Pedro], Colombo, R.[Roberto],
A Spectral Fitting Algorithm to Retrieve the Fluorescence Spectrum from Canopy Radiance,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909

Verrelst, J.[Jochem], Vicent, J.[Jorge], Rivera-Caicedo, J.P.[Juan Pablo], Lumbierres, M.[Maria], Morcillo-Pallarés, P.[Pablo], Moreno, J.[José],
Global Sensitivity Analysis of Leaf-Canopy-Atmosphere RTMs: Implications for Biophysical Variables Retrieval from Top-of-Atmosphere Radiance Data,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909

Dai, W.X.[Wen-Xia], Yang, B.S.[Bi-Sheng], Liang, X.L.[Xin-Lian], Dong, Z.[Zhen], Huang, R.G.[Rong-Gang], Wang, Y.S.[Yun-Sheng], Li, W.[Wuyan],
Automated fusion of forest airborne and terrestrial point clouds through canopy density analysis,
PandRS(156), 2019, pp. 94-107.
Elsevier DOI 1909
Airborne laser scanning (ALS), Terrestrial laser scanning (TLS), Forest, Point clouds, Registration BibRef

Morcillo-Pallarés, P.[Pablo], Rivera-Caicedo, J.P.[Juan Pablo], Belda, S.[Santiago], de Grave, C.[Charlotte], Burriel, H.[Helena], Moreno, J.[Jose], Verrelst, J.[Jochem],
Quantifying the Robustness of Vegetation Indices through Global Sensitivity Analysis of Homogeneous and Forest Leaf-Canopy Radiative Transfer Models,
RS(11), No. 20, 2019, pp. xx-yy.
DOI Link 1910

Gara, T.W.[Tawanda W.], Darvishzadeh, R.[Roshanak], Skidmore, A.K.[Andrew K.], Wang, T.J.[Tie-Jun], Heurich, M.[Marco],
Accurate modelling of canopy traits from seasonal Sentinel-2 imagery based on the vertical distribution of leaf traits,
PandRS(157), 2019, pp. 108-123.
Elsevier DOI 1911
Canopy traits, Sentinel 2 seasonality, Random forest, Vertical heterogeneity BibRef

Deepak, M.[Maya], Keski-Saari, S.[Sarita], Fauch, L.[Laure], Granlund, L.[Lars], Oksanen, E.[Elina], Keinänen, M.[Markku],
Leaf Canopy Layers Affect Spectral Reflectance in Silver Birch,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912

Pérez-Planells, L.[Lluís], Valor, E.[Enric], Niclòs, R.[Raquel], Coll, C.[César], Puchades, J.[Jesús], Campos-Taberner, M.[Manuel],
Evaluation of Six Directional Canopy Emissivity Models in the Thermal Infrared Using Emissivity Measurements,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912

Liu, Q., Fu, L., Wang, G., Li, S., Li, Z., Chen, E., Pang, Y., Hu, K.,
Improving Estimation of Forest Canopy Cover by Introducing Loss Ratio of Laser Pulses Using Airborne LiDAR,
GeoRS(58), No. 1, January 2020, pp. 567-585.
Forestry, Laser radar, Estimation, Biological system modeling, Vegetation, Lasers, loss ratio of laser pulses BibRef

Jiang, Y.[Yu], Snider, J.L.[John L.], Li, C.Y.[Chang-Ying], Rains, G.C.[Glen C.], Paterson, A.H.[Andrew H.],
Ground Based Hyperspectral Imaging to Characterize Canopy-Level Photosynthetic Activities,
RS(12), No. 2, 2020, pp. xx-yy.
DOI Link 2001

Fletcher, A.[Andrew], Mather, R.[Richard],
Hypertemporal Imaging Capability of UAS Improves Photogrammetric Tree Canopy Models,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004

Kokubu, Y.[Yutaka], Hara, S.[Seiichi], Tani, A.[Akira],
Mapping Seasonal Tree Canopy Cover and Leaf Area Using Worldview-2/3 Satellite Imagery: A Megacity-Scale Case Study in Tokyo Urban Area,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005

Rahman, M.M.[Md Mizanur], Zhang, X.[Xunhe], Ahmed, I.[Imran], Iqbal, Z.[Zaheer], Zeraatpisheh, M.[Mojtaba], Kanzaki, M.[Mamoru], Xu, M.[Ming],
Remote Sensing-Based Mapping of Senescent Leaf C:N Ratio in the Sundarbans Reserved Forest Using Machine Learning Techniques,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005

Gajardo, J.[John], Riaño, D.[David], García, M.[Mariano], Salas, J.[Javier], Martín, M.P.[M. Pilar],
Estimation of Canopy Gap Fraction from Terrestrial Laser Scanner Using an Angular Grid to Take Advantage of the Full Data Spatial Resolution,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006

Lim, J.B.[Joong-Bin], Kim, K.M.[Kyoung-Min], Kim, E.H.[Eun-Hee], Jin, R.[Ri],
Machine Learning for Tree Species Classification using Sentinel-2 Spectral Information, Crown Texture, and Environmental Variables,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006

Eskandari, S.[Saeedeh], Jaafari, M.R.[Mohammad Reza], Oliva, P.[Patricia], Ghorbanzadeh, O.[Omid], Blaschke, T.[Thomas],
Mapping Land Cover and Tree Canopy Cover in Zagros Forests of Iran: Application of Sentinel-2, Google Earth, and Field Data,
RS(12), No. 12, 2020, pp. xx-yy.
DOI Link 2006

Miraglio, T.[Thomas], Adeline, K.[Karine], Huesca, M.[Margarita], Ustin, S.[Susan], Briottet, X.[Xavier],
Joint Use of PROSAIL and DART for Fast LUT Building: Application to Gap Fraction and Leaf Biochemistry Estimations over Sparse Oak Stands,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009

Prada, M.[Marta], Cabo, C.[Carlos], Hernández-Clemente, R.[Rocío], Hornero, A.[Alberto], Majada, J.[Juan], Martínez-Alonso, C.[Celia],
Assessing Canopy Responses to Thinnings for Sweet Chestnut Coppice with Time-Series Vegetation Indices Derived from Landsat-8 and Sentinel-2 Imagery,
RS(12), No. 18, 2020, pp. xx-yy.
DOI Link 2009

Slavík, M.[Martin], Kuželka, K.[Karel], Modlinger, R.[Roman], Tomášková, I.[Ivana], Surový, P.[Peter],
UAV Laser Scans Allow Detection of Morphological Changes in Tree Canopy,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011

Pilaš, I.[Ivan], Gašparovic, M.[Mateo], Novkinic, A.[Alan], Klobucar, D.[Damir],
Mapping of the Canopy Openings in Mixed Beech-Fir Forest at Sentinel-2 Subpixel Level Using UAV and Machine Learning Approach,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012

Liu, W.W.[Wei-Wei], Luo, S.Z.[She-Zhou], Lu, X.L.[Xiao-Liang], Atherton, J.[Jon], Gastellu-Etchegorry, J.P.[Jean-Philippe],
Simulation-Based Evaluation of the Estimation Methods of Far-Red Solar-Induced Chlorophyll Fluorescence Escape Probability in Discontinuous Forest Canopies,
RS(12), No. 23, 2020, pp. xx-yy.
DOI Link 2012

Chang, M.[Ming], Zhu, S.J.[Sheng-Jie], Cao, J.C.[Jia-Chen], Chen, B.Y.[Bing-Yin], Zhang, Q.[Qi], Chen, W.H.[Wei-Hua], Jia, S.[Shiguo], Krishnan, P.[Padmaja], Wang, X.M.[Xue-Mei],
Improvement and Impacts of Forest Canopy Parameters on Noah-MP Land Surface Model from UAV-Based Photogrammetry,
RS(12), No. 24, 2020, pp. xx-yy.
DOI Link 2012

Richter, R.[Ronny], Hutengs, C.[Christopher], Wirth, C.[Christian], Bannehr, L.[Lutz], Vohland, M.[Michael],
Detecting Tree Species Effects on Forest Canopy Temperatures with Thermal Remote Sensing: The Role of Spatial Resolution,
RS(13), No. 1, 2021, pp. xx-yy.
DOI Link 2101

Du, K.[Kai], Huang, H.G.[Hua-Guo], Feng, Z.Y.[Zi-Yi], Hakala, T.[Teemu], Chen, Y.W.[Yu-Wei], Hyyppä, J.[Juha],
Using Microwave Profile Radar to Estimate Forest Canopy Leaf Area Index: Linking 3D Radiative Transfer Model and Forest Gap Model,
RS(13), No. 2, 2021, pp. xx-yy.
DOI Link 2101

Kopacková-Strnadová, V.[Veronika], Koucká, L.[Lucie], Jelének, J.[Jan], Lhotáková, Z.[Zuzana], Oulehle, F.[Filip],
Canopy Top, Height and Photosynthetic Pigment Estimation Using Parrot Sequoia Multispectral Imagery and the Unmanned Aerial Vehicle (UAV),
RS(13), No. 4, 2021, pp. xx-yy.
DOI Link 2103

Shi, H.Y.[Han-Yu], Xiao, Z.Q.[Zhi-Qiang],
The 4SAILT Model: An Improved 4SAIL Canopy Radiative Transfer Model for Sloping Terrain,
GeoRS(59), No. 7, July 2021, pp. 5515-5525.
Surface topography, Adaptive optics, Optical scattering, Solid modeling, Mathematical model, 4SAIL, topography BibRef

Gao, X.Y.[Xue-Yan], Li, C.[Chong], Cai, Y.[Yue], Ye, L.[Lei], Xiao, L.D.[Long-Dong], Zhou, G.[Guomo], Zhou, Y.F.[Yu-Feng],
Influence of Scale Effect of Canopy Projection on Understory Microclimate in Three Subtropical Urban Broad-Leaved Forests,
RS(13), No. 18, 2021, pp. xx-yy.
DOI Link 2109

Pu, Y.H.[Yi-Han], Xu, D.D.[Dan-Dan], Wang, H.B.[Hao-Bin], An, D.S.[De-Shuai], Xu, X.[Xia],
Extracting Canopy Closure by the CHM-Based and SHP-Based Methods with a Hemispherical FOV from UAV-LiDAR Data in a Poplar Plantation,
RS(13), No. 19, 2021, pp. xx-yy.
DOI Link 2110

Yu, F.Y.[Fang-Yuan], Gara, T.W.[Tawanda W.], Lian, J.[Juyu], Ye, W.[Wanhui], Shen, J.[Jian], Wang, T.J.[Tie-Jun], Wu, Z.F.[Zhi-Feng], Wang, J.J.[Jun-Jie],
Understanding the Impact of Vertical Canopy Position on Leaf Spectra and Traits in an Evergreen Broadleaved Forest,
RS(13), No. 24, 2021, pp. xx-yy.
DOI Link 2112

Ross, C.W.[C. Wade], Loudermilk, E.L.[E. Louise], Skowronski, N.[Nicholas], Pokswinski, S.[Scott], Hiers, J.K.[J. Kevin], O'Brien, J.[Joseph],
LiDAR Voxel-Size Optimization for Canopy Gap Estimation,
RS(14), No. 5, 2022, pp. xx-yy.
DOI Link 2203

Harris, R.C.[Ryley C.], Kennedy, L.M.[Lisa M.], Pingel, T.J.[Thomas J.], Thomas, V.A.[Valerie A.],
Assessment of Canopy Health with Drone-Based Orthoimagery in a Southern Appalachian Red Spruce Forest,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204

Nasiri, V.[Vahid], Darvishsefat, A.A.[Ali Asghar], Arefi, H.[Hossein], Griess, V.C.[Verena C.], Sadeghi, S.M.M.[Seyed Mohammad Moein], Borz, S.A.[Stelian Alexandru],
Modeling Forest Canopy Cover: A Synergistic Use of Sentinel-2, Aerial Photogrammetry Data, and Machine Learning,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204

Verhegghen, A.[Astrid], Kuzelova, K.[Klara], Syrris, V.[Vasileios], Eva, H.[Hugh], Achard, F.[Frédéric],
Mapping Canopy Cover in African Dry Forests from the Combined Use of Sentinel-1 and Sentinel-2 Data: Application to Tanzania for the Year 2018,
RS(14), No. 6, 2022, pp. xx-yy.
DOI Link 2204

Xie, B.[Bo], Cao, C.X.[Chun-Xiang], Xu, M.[Min], Yang, X.W.[Xin-Wei], Duerler, R.S.[Robert Shea], Bashir, B.[Barjeece], Huang, Z.B.[Zhi-Bni], Wang, K.[Kaimin], Chen, Y.[Yiyu], Guo, H.[Heyi],
Improved Forest Canopy Closure Estimation Using Multispectral Satellite Imagery within Google Earth Engine,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Yang, X.G.[Xi-Guang], He, P.[Ping], Yu, Y.[Ying], Fan, W.[Wenyi],
Stand Canopy Closure Estimation in Planted Forests Using a Geometric-Optical Model Based on Remote Sensing,
RS(14), No. 9, 2022, pp. xx-yy.
DOI Link 2205

Guan, P.[Peng], Zheng, Y.[Yili], Lei, G.[Guannan], Liu, Y.[Yang], Zhu, L.C.[Li-Chen], Guo, Y.[Youzheng], Wang, Y.[Yirui], Xi, B.[Benye],
Near-Earth Remote Sensing Images Used to Determine the Phenological Characteristics of the Canopy of Populus tomentosa B301 under Three Methods of Irrigation,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206
white poplar tree. BibRef

Sanchez-Azofeifa, A.[Arturo], Sharp, I.[Iain], Green, P.D.[Paul D.], Nightingale, J.[Joanne],
Calibration of Co-Located Identical PAR Sensors Using Wireless Sensor Networks and Characterization of the In Situ fPAR Variability in a Tropical Dry Forest,
RS(14), No. 12, 2022, pp. xx-yy.
DOI Link 2206

Shestakova, T.A.[Tatiana A.], Mackey, B.[Brendan], Hugh, S.[Sonia], Dean, J.[Jackie], Kukavskaya, E.A.[Elena A.], Laflamme, J.[Jocelyne], Shvetsov, E.G.[Evgeny G.], Rogers, B.M.[Brendan M.],
Mapping Forest Stability within Major Biomes Using Canopy Indices Derived from MODIS Time Series,
RS(14), No. 15, 2022, pp. xx-yy.
DOI Link 2208

Nasiri, V.[Vahid], Sadeghi, S.M.M.[Seyed Mohammad Moein], Moradi, F.[Fardin], Afshari, S.[Samaneh], Deljouei, A.[Azade], Griess, V.C.[Verena C.], Maftei, C.[Carmen], Borz, S.A.[Stelian Alexandru],
The Influence of Data Density and Integration on Forest Canopy Cover Mapping Using Sentinel-1 and Sentinel-2 Time Series in Mediterranean Oak Forests,
IJGI(11), No. 8, 2022, pp. xx-yy.
DOI Link 2209

Gao, T.[Ting], Gao, Z.H.[Zhi-Hai], Sun, B.[Bin], Qin, P.Y.[Peng-Yao], Li, Y.[Yifu], Yan, Z.Y.[Zi-Yu],
An Integrated Method for Estimating Forest-Canopy Closure Based on UAV LiDAR Data,
RS(14), No. 17, 2022, pp. xx-yy.
DOI Link 2209

Xia, J.S.[Ji-Sheng], Wang, Y.T.[Yu-Tong], Dong, P.L.[Pin-Liang], He, S.J.[Shi-Jun], Zhao, F.[Fei], Luan, G.Z.[Gui-Ze],
Object-Oriented Canopy Gap Extraction from UAV Images Based on Edge Enhancement,
RS(14), No. 19, 2022, pp. xx-yy.
DOI Link 2210

Bourassa, A.[Albert], Apparicio, P.[Philippe], Gelb, J.[Jérémy], Boisjoly, G.[Geneviève],
Canopy Assessment of Cycling Routes: Comparison of Videos from a Bicycle-Mounted Camera and GPS and Satellite Imagery,
IJGI(12), No. 1, 2023, pp. xx-yy.
DOI Link 2301

Liang, Z.G.[Zhi-Guo], Yu, Y.[Ying], Yang, X.[Xiguang], Fan, W.[Wenyi],
Comparison of Canopy Clumping Index Measuring Methods and Analysis of Their Impact,
RS(15), No. 2, 2023, pp. xx-yy.
DOI Link 2301

Chen, S.Q.[Shuai-Qiang], Chen, M.[Meng], Zhao, B.[Bingyu], Mao, T.[Ting], Wu, J.J.[Jian-Jun], Bao, W.X.[Wen-Xuan],
Urban Tree Canopy Mapping Based on Double-Branch Convolutional Neural Network and Multi-Temporal High Spatial Resolution Satellite Imagery,
RS(15), No. 3, 2023, pp. xx-yy.
DOI Link 2302

Jafarbiglu, H.[Hamid], Pourreza, A.[Alireza],
Impact of sun-view geometry on canopy spectral reflectance variability,
PandRS(196), 2023, pp. 270-286.
Elsevier DOI 2302
BRDF, Hotspot Effect, Radiometric Calibration, Directional Solar Radiation, Sun-View Angle Geometry BibRef

Narine, L.L.[Lana L.], Popescu, S.C.[Sorin C.], Malambo, L.[Lonesome],
A Methodological Framework for Mapping Canopy Cover Using ICESat-2 in the Southern USA,
RS(15), No. 6, 2023, pp. 1548.
DOI Link 2304

Shaik, R.U.[Riyaaz Uddien], Jallu, S.B.[Sriram Babu], Doctor, K.[Katarina],
Unveiling Temperature Patterns in Tree Canopies across Diverse Heights and Types,
RS(15), No. 8, 2023, pp. 2080.
DOI Link 2305

Kushwaha, S.K.P.[Sunni Kanta Prasad], Singh, A.[Arunima], Jain, K.[Kamal], Vybostok, J.[Jozef], Mokros, M.[Martin],
Qualitative Analysis of Tree Canopy Top Points Extraction from Different Terrestrial Laser Scanner Combinations in Forest Plots,
IJGI(12), No. 6, 2023, pp. xx-yy.
DOI Link 2307

Xiao, S.[Shunfu], Ye, Y.[Yulu], Fei, S.P.[Shuai-Peng], Chen, H.C.[Hao-Chong], zhang, B.[Bingyu], li, Q.[Qing], Cai, Z.B.[Zhi-Bo], Che, Y.[Yingpu], Wang, Q.[Qing], Ghafoor, A.[AbuZar], Bi, K.Y.[Kai-Yi], Shao, K.[Ke], Wang, R.[Ruili], Guo, Y.[Yan], Li, B.G.[Bao-Guo], Zhang, R.[Rui], Chen, Z.[Zhen], Ma, Y.T.[Yun-Tao],
High-throughput calculation of organ-scale traits with reconstructed accurate 3D canopy structures using a UAV RGB camera with an advanced cross-circling oblique route,
PandRS(201), 2023, pp. 104-122.
Elsevier DOI 2307
Field phenotyping, Canopy structure, Structure from motion, Oblique photography, Unmanned aerial vehicle, Organ-scale traits BibRef

Ziemer, J.[Jonas], Dubois, C.[Clémence], Thiel, C.[Christian], Bueso-Bello, J.L.[Jose-Luis], Rizzoli, P.[Paola], Schmullius, C.[Christiane],
Relationship between Lidar-Derived Canopy Densities and the Scattering Phase Center of High-Resolution TanDEM-X Data,
RS(15), No. 14, 2023, pp. 3589.
DOI Link 2307

Li, X.[Xiao], Li, L.Y.[Lin-Yuan], Ni, W.J.[Wen-Jian], Mu, X.[Xihan], Wu, X.D.[Xiao-Dan], Vaglio-Laurin, G.[Gaia], Vangi, E.[Elia], Stere?czak, K.[Krzysztof], Chirici, G.[Gherardo], Yu, S.[Shiyou], Huang, H.G.[Hua-Guo],
Validating GEDI tree canopy cover product across forest types using co-registered aerial LiDAR data,
PandRS(207), 2024, pp. 326-337.
Elsevier DOI 2401
tree canopy cover (TCC), GEDI product validation, aerial LiDAR, registration, forest type BibRef

Yang, X., Xi, X., Wang, C., Shi, J., Huang, Y.,
A Physical Inversion Method of Canopy FPAR from Airborne LIDAR Data And Ground Measurements,
DOI Link 2012

Erfanifard, Y., Khodaee, Z.,
Canopy Density Mapping on Ultracam-D Aerial Imagery in Zagros Woodlands, Iran,
DOI Link 1311

Duveiller, G., Defourny, P.,
Batch Processing of Hemispherical Photography Using Object-Based Image Analysis to Derive Canopy Biophysical Variables,
PDF File. 1007

Chapter on Cartography, Aerial Images, Buildings, Roads, Terrain, Forests, Trees, ATR continues in
Canopy Water Content .

Last update:Jun 5, 2024 at 10:22:22