22.5.11.5 Trees, Forest, Stem Volume, Biomass Measurements

Chapter Contents (Back)
Stem Volume. Forest. Biomass Measurement. LiDAR: See also Biomass Measurements, Forest, LiDAR Techniques, Airborne Laser. SAR Methods: See also Biomass Measurements, Forest, TanDEM-X, SAR, Radar Measurements. See also Biomass Measurements for Individual Trees. More for the tops than totally biomass: See also Trees, Forest Canopy Analysis. See also Forest Analysis, Terrestrial Laser Scanner, Terrestrial LiDAR, TLS.

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Dube, T.[Timothy], Mutanga, O.[Onisimo],
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Kim, G.[Ghiseok], Hong, S.J.[Suk-Ju], Lee, A.Y.[Ah-Yeong], Lee, Y.E.[Ye-Eun], Im, S.[Sangjun],
Moisture Content Measurement of Broadleaf Litters Using Near-Infrared Spectroscopy Technique,
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Hogland, J.[John], Anderson, N.[Nathaniel], Chung, W.[Woodam],
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Pandit, S.[Santa], Tsuyuki, S.[Satoshi], Dube, T.[Timothy],
Estimating Above-Ground Biomass in Sub-Tropical Buffer Zone Community Forests, Nepal, Using Sentinel 2 Data,
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Pandit, S.[Santa], Tsuyuki, S.[Satoshi], Dube, T.[Timothy],
Landscape-Scale Aboveground Biomass Estimation in Buffer Zone Community Forests of Central Nepal: Coupling In Situ Measurements with Landsat 8 Satellite Data,
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Knapp, N.[Nikolai], Huth, A.[Andreas], Kugler, F.[Florian], Papathanassiou, K.[Konstantinos], Condit, R.[Richard], Hubbell, S.P.[Stephen P.], Fischer, R.[Rico],
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Li, Y.G.[Yang-Guang], Han, N.[Ning], Li, X.J.[Xue-Jian], Du, H.Q.[Hua-Qiang], Mao, F.J.[Fang-Jie], Cui, L.[Lu], Liu, T.Y.[Teng-Yan], Xing, L.[Luqi],
Spatiotemporal Estimation of Bamboo Forest Aboveground Carbon Storage Based on Landsat Data in Zhejiang, China,
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Le, A.V.[Anh V.], Paull, D.J.[David J.], Griffin, A.L.[Amy L.],
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Nguyen, T.H.[Trung H.], Jones, S.[Simon], Soto-Berelov, M.[Mariela], Haywood, A.[Andrew], Hislop, S.[Samuel],
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Lin, J.Y.[Jia-Yuan], Wang, M.M.[Mei-Mei], Ma, M.[Mingguo], Lin, Y.[Yi],
Aboveground Tree Biomass Estimation of Sparse Subalpine Coniferous Forest with UAV Oblique Photography,
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Saarela, S.[Svetlana], Holm, S.[Sören], Healey, S.P.[Sean P.], Andersen, H.E.[Hans-Erik], Petersson, H.[Hans], Prentius, W.[Wilmer], Patterson, P.L.[Paul L.], Næsset, E.[Erik], Gregoire, T.G.[Timothy G.], Ståhl, G.[Göran],
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Improving Forest Aboveground Biomass Estimation of Pinus densata Forest in Yunnan of Southwest China by Spatial Regression using Landsat 8 Images,
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BibRef

Zhang, Y.[Yuzhen], Liang, S.L.[Shun-Lin], Yang, L.[Lu],
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Zhang, Q.[Qi], Xu, L.H.[Li-Hua], Zhang, M.Z.[Mao-Zhen], Wang, Z.[Zhi], Gu, Z.F.[Zhang-Feng], Wu, Y.[Yaqi], Shi, Y.J.[Yi-Jun], Lu, Z.[Zhangwei],
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Bascietto, M.[Marco], Sperandio, G.[Giulio], Bajocco, S.[Sofia],
Efficient Estimation of Biomass from Residual Agroforestry,
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Hu, Y.[Yang], Xu, X.L.[Xue-Lei], Wu, F.Y.[Fa-Yun], Sun, Z.Q.[Zhong-Qiu], Xia, H.M.[Hao-Ming], Meng, Q.M.[Qing-Min], Huang, W.L.[Wen-Li], Zhou, H.[Hua], Gao, J.P.[Jin-Ping], Li, W.[Weitao], Peng, D.[Daoli], Xiao, X.M.[Xiang-Ming],
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Jurjevic, L.[Luka], Gašparovic, M.[Mateo], Milas, A.S.[Anita Simic], Balenovic, I.[Ivan],
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RS(12), No. 3, 2020, pp. xx-yy.
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Li, X.Y.[Xin-Yu], Liu, Z.H.[Zhao-Hua], Lin, H.[Hui], Wang, G.X.[Guang-Xing], Sun, H.[Hua], Long, J.P.[Jiang-Ping], Zhang, M.[Meng],
Estimating the Growing Stem Volume of Chinese Pine and Larch Plantations based on Fused Optical Data Using an Improved Variable Screening Method and Stacking Algorithm,
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BibRef

Dong, L.F.[Luo-Fan], Du, H.Q.[Hua-Qiang], Han, N.[Ning], Li, X.J.[Xue-Jian], Zhu, D.[Di'en], Mao, F.J.[Fang-Jie], Zhang, M.[Meng], Zheng, J.L.[Jun-Long], Liu, H.[Hua], Huang, Z.[Zihao], He, S.B.[Shao-Bai],
Application of Convolutional Neural Network on Lei Bamboo Above-Ground-Biomass (AGB) Estimation Using Worldview-2,
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Poley, L.G.[Lucy G.], McDermid, G.J.[Gregory J.],
A Systematic Review of the Factors Influencing the Estimation of Vegetation Aboveground Biomass Using Unmanned Aerial Systems,
RS(12), No. 7, 2020, pp. xx-yy.
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BibRef

Pham, T.D.[Tien Dat], Yokoya, N.[Naoto], Xia, J.[Junshi], Ha, N.T.[Nam Thang], Le, N.N.[Nga Nhu], Nguyen, T.T.T.[Thi Thu Trang], Dao, T.H.[Thi Huong], Vu, T.T.P.[Thuy Thi Phuong], Pham, T.D.[Tien Duc], Takeuchi, W.[Wataru],
Comparison of Machine Learning Methods for Estimating Mangrove Above-Ground Biomass Using Multiple Source Remote Sensing Data in the Red River Delta Biosphere Reserve, Vietnam,
RS(12), No. 8, 2020, pp. xx-yy.
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Sánchez-Ruiz, S.[Sergio], Maselli, F.[Fabio], Chiesi, M.[Marta], Fibbi, L.[Luca], Martínez, B.[Beatriz], Campos-Taberner, M.[Manuel], García-Haro, F.J.[Francisco Javier], Gilabert, M.A.[María Amparo],
Remote Sensing and Bio-Geochemical Modeling of Forest Carbon Storage in Spain,
RS(12), No. 9, 2020, pp. xx-yy.
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Iizuka, K.[Kotaro], Hayakawa, Y.S.[Yuichi S.], Ogura, T.[Takuro], Nakata, Y.[Yasutaka], Kosugi, Y.[Yoshiko], Yonehara, T.[Taichiro],
Integration of Multi-Sensor Data to Estimate Plot-Level Stem Volume Using Machine Learning Algorithms-Case Study of Evergreen Conifer Planted Forests in Japan,
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Narine, L.L.[Lana L.], Popescu, S.C.[Sorin C.], Malambo, L.[Lonesome],
Using ICESat-2 to Estimate and Map Forest Aboveground Biomass: A First Example,
RS(12), No. 11, 2020, pp. xx-yy.
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Issa, S.[Salem], Dahy, B.[Basam], Ksiksi, T.[Taoufik], Saleous, N.[Nazmi],
A Review of Terrestrial Carbon Assessment Methods Using Geo-Spatial Technologies with Emphasis on Arid Lands,
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DOI Link 2006
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Poley, L.G.[Lucy G.], Laskin, D.N.[David N.], McDermid, G.J.[Gregory J.],
Quantifying Aboveground Biomass of Shrubs Using Spectral and Structural Metrics Derived from UAS Imagery,
RS(12), No. 14, 2020, pp. xx-yy.
DOI Link 2007
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Rodríguez-Veiga, P.[Pedro], Carreiras, J.[Joao], Smallman, T.L.[Thomas Luke], Exbrayat, J.F.[Jean-François], Ndambiri, J.[Jamleck], Mutwiri, F.[Faith], Nyasaka, D.[Divinah], Quegan, S.[Shaun], Williams, M.[Mathew], Balzter, H.[Heiko],
Carbon Stocks and Fluxes in Kenyan Forests and Wooded Grasslands Derived from Earth Observation and Model-Data Fusion,
RS(12), No. 15, 2020, pp. xx-yy.
DOI Link 2008
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Gao, Y.K.[Yu-Kun], Lu, D.S.[Deng-Sheng], Li, G.Y.[Gui-Ying], Wang, G.X.[Guang-Xing], Chen, Q.[Qi], Liu, L.J.[Li-Juan], Li, D.Q.[Deng-Qiu],
Comparative Analysis of Modeling Algorithms for Forest Aboveground Biomass Estimation in a Subtropical Region,
RS(10), No. 4, 2018, pp. xx-yy.
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Zahriban Heasari, M., Fallah, A., Shataee, S., Kalbi, S., Persson, H.,
Estimating The Forest Stand Volume and Basal Area Using Pleiades Spectral and Auxiliary Data,
SMPR19(1131-1136).
DOI Link 1912
BibRef

Jiang, S., Yao, W., Heurich, M.,
Dead Wood Detection Based On Semantic Segmentation of VHR Aerial CIR Imagery Using Optimized Fcn-densenet,
PIA19(127-133).
DOI Link 1912
BibRef

Torabzadeh, H., Moradi, M., Fatehi, P.,
Estimating Aboveground Biomass in Zagros Forest, Iran, Using Sentinel-2 Data,
SMPR19(1059-1063).
DOI Link 1912
BibRef

Tavasoli, N., Arefi, H., Samiei-Esfahany, S., Ronoud, Q.,
Modelling The Amount of Carbon Stock Using Remote Sensing in Urban Forest and Its Relationship With Land Use Change,
SMPR19(1051-1058).
DOI Link 1912
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Alboabidallah, A., Martin, J., Lavender, S., Abbott, V.,
Using Landsat-8 and Sentinel-1 data for Above Ground Biomass assessment in the Tamar valley and Dartmoor,
MultiTemp17(1-7)
IEEE DOI 1712
vegetation mapping, ANOVA analysis, Dartmoor, Landsat-8 Data, Local Heights range analysis, NDVI multi-temporal range, Sentinel-1 BibRef

Li, Y., Zhang, H., Yang, T.D.[Ting-Dong], Ma, Z.Y.[Zai-Yang],
Visual simulation of interactive process of stand growth, structure and thinning,
ICIVC17(746-755)
IEEE DOI 1708
Analytical models, C# languages, Computational modeling, Semantics, Syntactics, Visualization, interactive thinning, removed trees, stand growth, stand structure, visual, simulation BibRef

Mokroš, M., Tabacák, M., Lieskovský, M., Fabrika, M.,
Unmanned Aerial Vehicle Use For Wood Chips Pile Volume Estimation,
ISPRS16(B1: 953-956).
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Akca, D.[Devrim], Stylianidis, E.[Efstratios], Smagas, K.[Konstantinos], Hofer, M.[Martin], Poli, D.[Daniela], Gruen, A.[Armin], Martin, V.S.[Victor Sanchez], Altan, O.[Orhan], Walli, A.[Andreas], Jimeno, E.[Elisa], Garcia, A.[Alejandro],
Volumetric Forest Change Detection Through Vhr Satellite Imagery,
ISPRS16(B8: 1213-1220).
DOI Link 1610
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Safari, A., Sohrabi, H.,
Ability of Landsat-8 OLI Derived Texture Metrics In Estimating Aboveground Carbon Stocks Of Coppice Oak Forests,
ISPRS16(B8: 751-754).
DOI Link 1610
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Kim, K.M.,
Estimation Of Stand Height And Forest Volume Using High Resolution Stereo Photography And Forest Type Map,
ISPRS16(B8: 695-698).
DOI Link 1610
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Patias, P.[Petros], Stournara, P.[Panagiota],
Estimating Wood Volume For Pinus Brutia Trees In Forest Stands From Quickbird-2 Imagery,
ISPRS16(B7: 329-334).
DOI Link 1610
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Xing, Y.Q.[Yan-Qiu], Qiu, S.[Sai], Ding, J.H.[Jian-Hua], Tian, J.[Jing],
Estimation Of Regional Forest Aboveground Biomass Combining Icesat-glas Waveforms And Hj-1a/hsi Hyperspectral Imageries,
ISPRS16(B7: 731-737).
DOI Link 1610
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Karpina, M., Jarzabek-Rychard, M., Tymków, P., Borkowski, A.,
UAV-based Automatic Tree Growth Measurement For Biomass Estimation,
ISPRS16(B8: 685-688).
DOI Link 1610
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de Keersmaecker, W., Lhermitte, S., Tits, L., Honnay, O., Coppin, P., Somers, B.,
Towards the large-scale assessment of vegetation biomass production stability,
MultiTemp15(1-4)
IEEE DOI 1511
Monte Carlo methods BibRef

Berveglieri, A., Oliveira, R.O., Tommaselli, A.M.G.,
A feasibility study on the measurement of tree trunks in forests using multi-scale vertical images,
CloseRange14(87-92).
DOI Link 1411
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Mizoguchi, T., Kobayashi, Y.,
Interactive Trunk Extraction from Forest Point Cloud,
CloseRange14(433-436).
DOI Link 1411
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Steensen, T., Müller, S., Jandewerth, M., Büscher, O.,
Mapping Biomass Availability to Decrease the Dependency on Fossil Fuels,
Thematic14(165-171).
DOI Link 1404
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Boesch, R.,
Model Based Automatic Segmentation of Tree Stems from Single Scan Data,
SSG13(49-53).
DOI Link 1402
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Müller, S., Büscher, O., Jandewerth, M.,
Estimation of Biomass Potential Based on Classification and Height Information,
Hannover13(263-268).
DOI Link 1308
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Amarsaikhan, D., Saandar, M., Battsengel, V., Amarjargal, S.,
Forest Resources Study In Mongolia Using Advanced Spatial Technologies,
ISPRS12(XXXIX-B7:257-262).
DOI Link 1209
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Sohrabi, H.,
Estimating Mixed Broadleaves Forest Stand Volume Using DSM Extracted From Digital Aerial Images,
ISPRS12(XXXIX-B8:437-440).
DOI Link 1209
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Uramoto, Y., Zhu, L., Tachibana, K., Shimamura, H., Ogaya, N.,
Development Of Photogrammetry System For Grasping Forest Resources Information,
ISPRS12(XXXIX-B8:447-450).
DOI Link 1209
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Sah, B.P., Hämäläinen, J.M., Sah, A.K., Honji, K., Foli, E.G., Awudi, C.,
The Use Of Satellite Imagery To Guide Field Plot Sampling Scheme For Biomass Estimation In Ghanaian Forest,
AnnalsPRS(I-4), No. 2012, pp. 221-226.
HTML Version. 1209
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Perry, E.M., Fitzgerald, G.J., Poole, N., Craig, S., Whitlock, A.,
NDVI from Active Optical Sensors As A Measure Of Canopy Cover And Biomass,
ISPRS12(XXXIX-B8:317-319).
DOI Link 1209
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Forsman, M., Börlin, N., Holmgren, J.,
Estimation Of Tree Stem Attributes Using Terrestrial Photogrammetry,
ISPRS12(XXXIX-B5:261-265).
DOI Link 1209
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Kamiya, T., Koizumi, H., Wang, J., Itaya, A.,
Forest Resource Management System By Standing Tree Volume Estimation Using Aerial Stereo Photos,
ISPRS12(XXXIX-B8:413-417).
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Vock, D., Gumhold, S., Spehr, M., Westfield, P., Maas, H.G.,
GPU-based Volumetric Reconstruction Of Trees From Multiple Images,
CloseRange10(xx-yy).
PDF File. 1006
See also Automatic Feature Matching Between Digital Images And 2d Representations Of A 3d Laser Scanner Point Cloud. BibRef

Rosette, J., North, P., Suárez, J.,
A Method of Directly Estimating Stemwood Volume from GLAS Waveform Parameters,
Laser07(344).
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Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Canopy Height Measurement .


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