22.5.11.5.3 Biomass Measurements, Forest, LiDAR Techniques, Airborne Laser

Chapter Contents (Back)
Biomass Measurement. LIDAR. Ground-lever Laser/LiDAR: See also Biomass Measurements, Forest, Terrestial Laser Techniques. The general methods. See also Trees, Forest, Stem Volume, Biomass Measurements.

Maselli, F.[Fabio], Chiesi, M.[Marta],
Evaluation of Statistical Methods to Estimate Forest Volume in a Mediterranean Region,
GeoRS(44), No. 8, August 2006, pp. 2239-2250.
IEEE DOI 0608
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 1110
Stem volume; LiDAR; Landsat ETM+; k-NN; Local regression BibRef

van Aardt, J.A.N.[Jan A.N.], Wynne, R.H.[Randolph H.], Scrivani, J.A.[John A.],
Lidar-based Mapping of Forest Volume and Biomass by Taxonomic Group Using Structurally Homogenous Segments,
PhEngRS(74), No. 8, August 2008, pp. 1033-1044.
WWW Link. 0804
An evaluation of an object-oriented approach to deciduous and coniferous forest classification, as well as volume and biomass estimation, using small-footprint lidar height and intensity distributions, and highlights of the potential of perobject lidar data analysis for stand-level forest inventories. BibRef

Hecht, R., Meinel, G., Buchroithner, M.F.,
Estimation of Urban Green Volume Based on Single-Pulse LiDAR Data,
GeoRS(46), No. 11, November 2008, pp. 3832-3840.
IEEE DOI 0812
BibRef

Dalponte, M.[Michele], Martinez, C.[Cristina], Rodeghiero, M.[Mirco], Gianelle, D.[Damiano],
The role of ground reference data collection in the prediction of stem volume with LiDAR data in mountain areas,
PandRS(66), No. 6, November 2011, pp. 787-797.
Elsevier DOI 1112
LiDAR; Forestry; Reference data; Forest inventory design; Prediction BibRef

Matikainen, L.[Leena], Karila, K.[Kirsi], Litkey, P.[Paula], Ahokas, E.[Eero], Hyyppä, J.[Juha],
Combining single photon and multispectral airborne laser scanning for land cover classification,
PandRS(164), 2020, pp. 200-216.
Elsevier DOI 2005
Laser scanning, Lidar, Single photon, Multispectral, Land cover, Classification BibRef

Niska, H., Skon, J.P., Packalen, P., Tokola, T., Maltamo, M., Kolehmainen, M.,
Neural Networks for the Prediction of Species-Specific Plot Volumes Using Airborne Laser Scanning and Aerial Photographs,
GeoRS(48), No. 3, March 2010, pp. 1076-1085.
IEEE DOI 1003
BibRef

Kankare, V.[Ville], Vauhkonen, J.[Jari], Tanhuanpää, T.[Topi], Holopainen, M.[Markus], Vastaranta, M.[Mikko], Joensuu, M.[Marianna], Krooks, A.[Anssi], Hyyppä, J.[Juha], Hyyppä, H.[Hannu], Alho, P.[Petteri], Viitala, R.[Risto],
Accuracy in Estimation of Timber Assortments and Stem Distribution: A Comparison of Airborne and Terrestrial Laser Scanning Techniques,
PandRS(97), No. 1, 2014, pp. 89-97.
Elsevier DOI 1410
Stem distribution BibRef

Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Litkey, P.[Paula], Kaartinen, H.[Harri], Vastaranta, M.[Mikko], Holopainen, M.[Markus],
Single-Sensor Solution to Tree Species Classification Using Multispectral Airborne Laser Scanning,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

Ahokas, E.[Eero], Hyyppä, J.[Juha], Yu, X., Liang, X.L.[Xin-Lian], Matikainen, L.[Leena], Karila, K.[Kirsi], Litkey, P.[Paula], Kukko, A., Jaakkola, A., Kaartinen, H., Holopainen, M., Vastaranta, M.,
Towards Automatic Single-sensor Mapping By Multispectral Airborne Laser Scanning,
ISPRS16(B3: 155-162).
DOI Link 1610
BibRef

Treitz, P., Lim, K., Woods, M., Pitt, D., Nesbitt, D., Etheridge, D.,
LiDAR Sampling Density for Forest Resource Inventories in Ontario, Canada,
RS(4), No. 4, April 2012, pp. 830-848.
DOI Link 1202
BibRef

Lindberg, E., Hollaus, M.,
Comparison of Methods for Estimation of Stem Volume, Stem Number and Basal Area from Airborne Laser Scanning Data in a Hemi-Boreal Forest,
RS(4), No. 4, April 2012, pp. 1004-1023.
DOI Link 1202
BibRef

Hyyppä, J., Yu, X., Hyyppä, H., Vastaranta, M., Holopainen, M., Kukko, A., Kaartinen, H., Jaakkola, A., Vaaja, M., Koskinen, J., Alho, P.,
Advances in Forest Inventory Using Airborne Laser Scanning,
RS(4), No. 5, May 2012, pp. 1190-1207.
DOI Link 1205
BibRef

Estornell, J., Ruiz, L.A., Velázquez-Martí, B., Hermosilla, T.,
Assessment of factors affecting shrub volume estimations using airborne discrete-return LiDAR data in Mediterranean areas,
AppRS(6), 2012, pp. 063544.
WWW Link. 1210
BibRef

Straub, C.[Christoph], Dees, M.[Matthias], Weinacker, H.[Holger], Koch, B.[Barbara],
Using Airborne Laser Scanner Data and CIR Orthophotos to Estimate the Stem Volume of Forest Stands,
PFG(2009), No. 3, 2009, pp. 277-287.
WWW Link. 1211
BibRef

Estornell, J., Ruiz, L.A., Velázquez-Martí, B., Hermosilla, T.,
Estimation of biomass and volume of shrub vegetation using LiDAR and spectral data in a Mediterranean environment,
Biomass and Bioenergy(46), 2012, pp. 710-721.
Elsevier DOI 1212
BibRef

Mora, B.[Brice], Wulder, M.A.[Michael A.], White, J.C.[Joanne C.], Hobart, G.[Geordie],
Modeling Stand Height, Volume, and Biomass from Very High Spatial Resolution Satellite Imagery and Samples of Airborne LiDAR,
RS(5), No. 5, 2013, pp. 2308-2326.
DOI Link 1307
BibRef

Rana, P.[Parvez], Tokola, T.[Timo], Korhonen, L.[Lauri], Xu, Q.[Qing], Kumpula, T.[Timo], Vihervaara, P.[Petteri], Mononen, L.[Laura],
Training Area Concept in a Two-Phase Biomass Inventory Using Airborne Laser Scanning and RapidEye Satellite Data,
RS(6), No. 1, 2013, pp. 285-309.
DOI Link 1402
BibRef
And: Correction: RS(7), No. 8, 2015, pp. 10242.
DOI Link 1509
BibRef

Laurin, G.V.[Gaia Vaglio], Chen, Q.[Qi], Lindsell, J.A.[Jeremy A.], Coomes, D.A.[David A.], del Frate, F.[Fabio], Guerriero, L.[Leila], Pirotti, F.[Francesco], Valentini, R.[Riccardo],
Above ground biomass estimation in an African tropical forest with lidar and hyperspectral data,
PandRS(89), No. 1, 2014, pp. 49-58.
Elsevier DOI 1403
Lidar BibRef

Rana, P.[Parvez], Korhonen, L.[Lauri], Gautam, B.[Basanta], Tokola, T.[Timo],
Effect of field plot location on estimating tropical forest above-ground biomass in Nepal using airborne laser scanning data,
PandRS(94), No. 1, 2014, pp. 55-62.
Elsevier DOI 1407
ALS BibRef

Hernández-Stefanoni, J.L.[José Luis], Dupuy, J.M.[Juan Manuel], Johnson, K.D.[Kristofer D.], Birdsey, R.[Richard], Tun-Dzul, F.[Fernando], Peduzzi, A.[Alicia], Caamal-Sosa, J.P.[Juan Pablo], Sánchez-Santos, G.[Gonzalo], López-Merlín, D.[David],
Improving Species Diversity and Biomass Estimates of Tropical Dry Forests Using Airborne LiDAR,
RS(6), No. 6, 2014, pp. 4741-4763.
DOI Link 1407
BibRef

Wallace, L., Musk, R., Lucieer, A.,
An Assessment of the Repeatability of Automatic Forest Inventory Metrics Derived From UAV-Borne Laser Scanning Data,
GeoRS(52), No. 11, November 2014, pp. 7160-7169.
IEEE DOI 1407
Lasers BibRef

Cao, L.[Lin], Coops, N.C.[Nicholas C.], Hermosilla, T.[Txomin], Innes, J.[John], Dai, J.S.[Jin-Song], She, G.H.[Guang-Hui],
Using Small-Footprint Discrete and Full-Waveform Airborne LiDAR Metrics to Estimate Total Biomass and Biomass Components in Subtropical Forests,
RS(6), No. 8, 2014, pp. 7110-7135.
DOI Link 1410
BibRef

Pirotti, F.[Francesco], Laurin, G.V.[Gaia Vaglio], Vettore, A.[Antonio], Masiero, A.[Andrea], Valentini, R.[Riccardo],
Small Footprint Full-Waveform Metrics Contribution to the Prediction of Biomass in Tropical Forests,
RS(6), No. 10, 2014, pp. 9576-9599.
DOI Link 1411
BibRef

Schreyer, J.[Johannes], Tigges, J.[Jan], Lakes, T.[Tobia], Churkina, G.[Galina],
Using Airborne LiDAR and QuickBird Data for Modelling Urban Tree Carbon Storage and Its Distribution: A Case Study of Berlin,
RS(6), No. 11, 2014, pp. 10636-10655.
DOI Link 1412
BibRef

Hansen, E.H.[Endre Hofstad], Gobakken, T.[Terje], Bollandsås, O.M.[Ole Martin], Zahabu, E.[Eliakimu], Næsset, E.[Erik],
Modeling Aboveground Biomass in Dense Tropical Submontane Rainforest Using Airborne Laser Scanner Data,
RS(7), No. 1, 2015, pp. 788-807.
DOI Link 1502
BibRef

Sheridan, R.D.[Ryan D.], Popescu, S.C.[Sorin C.], Gatziolis, D.[Demetrios], Morgan, C.L.S.[Cristine L. S.], Ku, N.W.[Nian-Wei],
Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest,
RS(7), No. 1, 2014, pp. 229-255.
DOI Link 1502
BibRef

Singh, K.K.[Kunwar K.], Chen, G.[Gang], McCarter, J.B.[James B.], Meentemeyer, R.K.[Ross K.],
Effects of LiDAR point density and landscape context on estimates of urban forest biomass,
PandRS(101), No. 1, 2015, pp. 310-322.
Elsevier DOI 1503
LiDAR BibRef

Li, L.[Le], Guo, Q.H.[Qing-Hua], Tao, S.L.[Sheng-Li], Kelly, M.[Maggi], Xu, G.C.[Guang-Cai],
Lidar with multi-temporal MODIS provide a means to upscale predictions of forest biomass,
PandRS(102), No. 1, 2015, pp. 198-208.
Elsevier DOI 1503
Lidar BibRef

Ceballos, A.[Andrés], Hernández, J.[Jaime], Corvalán, P.[Patricio], Galleguillos, M.[Mauricio],
Comparison of Airborne LiDAR and Satellite Hyperspectral Remote Sensing to Estimate Vascular Plant Richness in Deciduous Mediterranean Forests of Central Chile,
RS(7), No. 3, 2015, pp. 2692-2714.
DOI Link 1504
BibRef

Badreldin, N.[Nasem], Sanchez-Azofeifa, G.A.[G. Arturo],
Estimating Forest Biomass Dynamics by Integrating Multi-Temporal Landsat Satellite Images with Ground and Airborne LiDAR Data in the Coal Valley Mine, Alberta, Canada,
RS(7), No. 3, 2015, pp. 2832-2849.
DOI Link 1504
BibRef

Medeiros, S.[Stephen], Hagen, S.[Scott], Weishampel, J.[John], Angelo, J.[James],
Adjusting Lidar-Derived Digital Terrain Models in Coastal Marshes Based on Estimated Aboveground Biomass Density,
RS(7), No. 4, 2015, pp. 3507-3525.
DOI Link 1505
BibRef

Chen, Q.[Qi],
Modeling aboveground tree woody biomass using national-scale allometric methods and airborne lidar,
PandRS(106), No. 1, 2015, pp. 95-106.
Elsevier DOI 1507
Biomass See also Assessment of terrain elevation derived from satellite laser altimetry over mountainous forest areas using airborne lidar data. BibRef

Véga, C.[Cédric], Vepakomma, U.[Udayalakshmi], Morel, J.[Jules], Bader, J.L.[Jean-Luc], Rajashekar, G.[Gopalakrishnan], Jha, C.S.[Chandra Shekhar], Ferêt, J.[Jérôme], Proisy, C.[Christophe], Pélissier, R.[Raphaël], Dadhwal, V.K.[Vinay Kumar],
Aboveground-Biomass Estimation of a Complex Tropical Forest in India Using Lidar,
RS(7), No. 8, 2015, pp. 10607.
DOI Link 1509
BibRef

Molina, P.X.[Patricio Xavier], Asner, G.P.[Gregory P.], Abadía, M.F.[Mercedes Farjas], Manrique, J.C.O.[Juan Carlos Ojeda], Diez, L.A.S.[Luis Alberto Sánchez], Valencia, R.[Renato],
Spatially-Explicit Testing of a General Aboveground Carbon Density Estimation Model in a Western Amazonian Forest Using Airborne LiDAR,
RS(8), No. 1, 2016, pp. 9.
DOI Link 1602
BibRef

Chen, Q.[Qi], Lu, D.S.[Deng-Sheng], Keller, M.[Michael], dos-Santos, M.N.[Maiza Nara], Bolfe, E.L.[Edson Luis], Feng, Y.[Yunyun], Wang, C.[Changwei],
Modeling and Mapping Agroforestry Aboveground Biomass in the Brazilian Amazon Using Airborne Lidar Data,
RS(8), No. 1, 2016, pp. 21.
DOI Link 1602
BibRef

Giannico, V.[Vincenzo], Lafortezza, R.[Raffaele], John, R.[Ranjeet], Sanesi, G.[Giovanni], Pesola, L.[Lucia], Chen, J.Q.[Ji-Quan],
Estimating Stand Volume and Above-Ground Biomass of Urban Forests Using LiDAR,
RS(8), No. 4, 2016, pp. 339.
DOI Link 1604
BibRef

Hu, T.Y.[Tian-Yu], Su, Y.J.[Yan-Jun], Xue, B.L.[Bao-Lin], Liu, J.[Jin], Zhao, X.Q.[Xiao-Qian], Fang, J.Y.[Jing-Yun], Guo, Q.H.[Qing-Hua],
Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data,
RS(8), No. 7, 2016, pp. 565.
DOI Link 1608
BibRef

Lin, C.S.[Chin-Su], Thomson, G.[Gavin], Popescu, S.C.[Sorin C.],
An IPCC-Compliant Technique for Forest Carbon Stock Assessment Using Airborne LiDAR-Derived Tree Metrics and Competition Index,
RS(8), No. 6, 2016, pp. 528.
DOI Link 1608
BibRef

Ferraz, A.[António], Saatchi, S.[Sassan], Mallet, C.[Clément], Jacquemoud, S.[Stéphane], Gonçalves, G.[Gil], Silva, C.A.[Carlos Alberto], Soares, P.[Paula], Tomé, M.[Margarida], Pereira, L.[Luisa],
Airborne Lidar Estimation of Aboveground Forest Biomass in the Absence of Field Inventory,
RS(8), No. 8, 2016, pp. 653.
DOI Link 1609
BibRef

Kramer, H.A.[Heather A.], Collins, B.M.[Brandon M.], Lake, F.K.[Frank K.], Jakubowski, M.K.[Marek K.], Stephens, S.L.[Scott L.], Kelly, M.[Maggi],
Estimating Ladder Fuels: A New Approach Combining Field Photography with LiDAR,
RS(8), No. 9, 2016, pp. 766.
DOI Link 1610
BibRef

Laurin, G.V.[Gaia Vaglio], Pirotti, F.[Francesco], Callegari, M.[Mattia], Chen, Q.[Qi], Cuozzo, G.[Giovanni], Lingua, E.[Emanuele], Notarnicola, C.[Claudia], Papale, D.[Dario],
Potential of ALOS2 and NDVI to Estimate Forest Above-Ground Biomass, and Comparison with Lidar-Derived Estimates,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Qian, C.[Chuang], Liu, H.[Hui], Tang, J.[Jian], Chen, Y.[Yuwei], Kaartinen, H.[Harri], Kukko, A.[Antero], Zhu, L.L.[Ling-Li], Liang, X.[Xinlian], Chen, L.[Liang], Hyyppä, J.[Juha],
An Integrated GNSS/INS/LiDAR-SLAM Positioning Method for Highly Accurate Forest Stem Mapping,
RS(9), No. 1, 2017, pp. xx-yy.
DOI Link 1702
BibRef

Kauranne, T.[Tuomo], Joshi, A.[Anup], Gautam, B.[Basanta], Manandhar, U.[Ugan], Nepal, S.[Santosh], Peuhkurinen, J.[Jussi], Hämäläinen, J.[Jarno], Junttila, V.[Virpi], Gunia, K.[Katja], Latva-Käyrä, P.[Petri], Kolesnikov, A.[Alexander], Tegel, K.[Katri], Leppänen, V.[Vesa],
LiDAR-Assisted Multi-Source Program (LAMP) for Measuring Above Ground Biomass and Forest Carbon,
RS(9), No. 2, 2017, pp. xx-yy.
DOI Link 1703
BibRef

El Hajj, M.[Mohammad], Baghdadi, N.[Nicolas], Fayad, I.[Ibrahim], Vieilledent, G.[Ghislain], Bailly, J.S.[Jean-Stéphane], Minh, D.H.T.[Dinh Ho Tong],
Interest of Integrating Spaceborne LiDAR Data to Improve the Estimation of Biomass in High Biomass Forested Areas,
RS(9), No. 3, 2017, pp. xx-yy.
DOI Link 1704
BibRef

Deo, R.K.[Ram K.], Russell, M.B.[Matthew B.], Domke, G.M.[Grant M.], Andersen, H.E.[Hans-Erik], Cohen, W.B.[Warren B.], Woodall, C.W.[Christopher W.],
Evaluating Site-Specific and Generic Spatial Models of Aboveground Forest Biomass Based on Landsat Time-Series and LiDAR Strip Samples in the Eastern USA,
RS(9), No. 6, 2017, pp. xx-yy.
DOI Link 1706
BibRef

Yoga, S.[Sarah], Bégin, J.[Jean], St-Onge, B.[Benoît], Riopel, M.[Martin],
Modeling the Effect of the Spatial Pattern of Airborne Lidar Returns on the Prediction and the Uncertainty of Timber Merchantable Volume,
RS(9), No. 8, 2017, pp. xx-yy.
DOI Link 1708
BibRef

Silva, C.A.[Carlos Alberto], Hudak, A.T.[Andrew Thomas], Vierling, L.A.[Lee Alexander], Klauberg, C.[Carine], Garcia, M.[Mariano], Ferraz, A.[António], Keller, M.[Michael], Eitel, J.[Jan], Saatchi, S.[Sassan],
Impacts of Airborne Lidar Pulse Density on Estimating Biomass Stocks and Changes in a Selectively Logged Tropical Forest,
RS(9), No. 10, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Li, A.[Aihua], Dhakal, S.[Shital], Glenn, N.F.[Nancy F.], Spaete, L.P.[Lucas P.], Shinneman, D.J.[Douglas J.], Pilliod, D.S.[David S.], Arkle, R.S.[Robert S.], McIlroy, S.K.[Susan K.],
Lidar Aboveground Vegetation Biomass Estimates in Shrublands: Prediction, Uncertainties and Application to Coarser Scales,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Spriggs, R.A.[Rebecca A.], Coomes, D.A.[David A.], Jones, T.A.[Trevor A.], Caspersen, J.P.[John P.], Vanderwel, M.C.[Mark C.],
An Alternative Approach to Using LiDAR Remote Sensing Data to Predict Stem Diameter Distributions across a Temperate Forest Landscape,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Rana, P.[Parvez], Vauhkonen, J.[Jari], Junttila, V.[Virpi], Hou, Z.Y.[Zheng-Yang], Gautam, B.[Basanta], Cawkwell, F.[Fiona], Tokola, T.[Timo],
Large tree diameter distribution modelling using sparse airborne laser scanning data in a subtropical forest in Nepal,
PandRS(134), No. Supplement C, 2017, pp. 86-95.
Elsevier DOI 1712
Diameter distribution, -MSN, Large tree, Nepal, Tropical forests, LiDAR BibRef

Fu, L.Y.[Li-Yong], Liu, Q.W.[Qing-Wang], Sun, H.[Hua], Wang, Q.Y.[Qiu-Yan], Li, Z.Y.[Zeng-Yuan], Chen, E.[Erxue], Pang, Y.[Yong], Song, X.Y.[Xin-Yu], Wang, G.X.[Guang-Xing],
Development of a System of Compatible Individual Tree Diameter and Aboveground Biomass Prediction Models Using Error-In-Variable Regression and Airborne LiDAR Data,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Pang, Y.[Yong], Li, Z.Y.[Zeng-Yuan],
Subtropical Forest Biomass Estimation Using Airborne Lidar And Hyperspectral Data,
ISPRS16(B8: 747-749).
DOI Link 1610
BibRef

Wang, M.J.[Meng-Jia], Sun, R.[Rui], Xiao, Z.Q.[Zhi-Qiang],
Estimation of Forest Canopy Height and Aboveground Biomass from Spaceborne LiDAR and Landsat Imageries in Maryland,
RS(10), No. 2, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Hirata, Y.[Yasumasa], Furuya, N.[Naoyuki], Saito, H.[Hideki], Pak, C.[Chealy], Leng, C.[Chivin], Sokh, H.[Heng], Ma, V.[Vuthy], Kajisa, T.[Tsuyoshi], Ota, T.[Tetsuji], Mizoue, N.[Nobuya],
Object-Based Mapping of Aboveground Biomass in Tropical Forests Using LiDAR and Very-High-Spatial-Resolution Satellite Data,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Tenneson, K.[Karis], Patterson, M.S.[Matthew S.], Mellin, T.[Thomas], Nigrelli, M.[Mark], Joria, P.[Peter], Mitchell, B.[Brent],
Development of a Regional LIDAR-Derived Above-Ground Biomass Model with Bayesian Model Averaging for Use in Ponderosa Pine and Mixed Conifer Forests in Arizona and New Mexico, USA,
RS(10), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Cao, L.[Luodan], Pan, J.J.[Jian-Jun], Li, R.J.[Rui-Juan], Li, J.[Jialin], Li, Z.[Zhaofu],
Integrating Airborne LiDAR and Optical Data to Estimate Forest Aboveground Biomass in Arid and Semi-Arid Regions of China,
RS(10), No. 4, 2018, pp. xx-yy.
DOI Link 1805
BibRef

González-Jaramillo, V.[Víctor], Fries, A.[Andreas], Zeilinger, J.[Jörg], Homeier, J.[Jürgen], Paladines-Benitez, J.[Jhoana], Bendix, J.[Jörg],
Estimation of Above Ground Biomass in a Tropical Mountain Forest in Southern Ecuador Using Airborne LiDAR Data,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Hernández-Stefanoni, J.L.[José Luis], Reyes-Palomeque, G.[Gabriela], Castillo-Santiago, M.Á.[Miguel Ángel], George-Chacón, S.P.[Stephanie P.], Huechacona-Ruiz, A.H.[Astrid Helena], Tun-Dzul, F.[Fernando], Rondon-Rivera, D.[Dinosca], Dupuy, J.M.[Juan Manuel],
Effects of Sample Plot Size and GPS Location Errors on Aboveground Biomass Estimates from LiDAR in Tropical Dry Forests,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Navarro-Cerrillo, R.M.[Rafael M.], Duque-Lazo, J.[Joaquín], Rodríguez-Vallejo, C.[Carlos], Varo-Martínez, M.Á.[M. Ángeles], Palacios-Rodríguez, G.[Guillermo],
Airborne Laser Scanning Cartography of On-Site Carbon Stocks as a Basis for the Silviculture of Pinus Halepensis Plantations,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Paris, C., Bruzzone, L.,
A Growth-Model-Driven Technique for Tree Stem Diameter Estimation by Using Airborne LiDAR Data,
GeoRS(57), No. 1, January 2019, pp. 76-92.
IEEE DOI 1901
Vegetation, Forestry, Laser radar, Estimation, Surfaces, Data mining, Data models, Forest parameters, forestry, tree stem attributes BibRef

Cao, L.[Lin], Zhang, Z.N.[Zheng-Nan], Yun, T.[Ting], Wang, G.B.[Gui-Bin], Ruan, H.H.[Hong-Hua], She, G.H.[Guang-Hui],
Estimating Tree Volume Distributions in Subtropical Forests Using Airborne LiDAR Data,
RS(11), No. 1, 2019, pp. xx-yy.
DOI Link 1901
BibRef

Sun, X.F.[Xiao-Fang], Li, G.[Guicai], Wang, M.[Meng], Fan, Z.[Zemeng],
Analyzing the Uncertainty of Estimating Forest Aboveground Biomass Using Optical Imagery and Spaceborne LiDAR,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Wang, M.X.[Meng-Xi], Liu, Q.W.[Qing-Wang], Fu, L.Y.[Li-Yong], Wang, G.X.[Guang-Xing], Zhang, X.Q.[Xiong-Qing],
Airborne LIDAR-Derived Aboveground Biomass Estimates Using a Hierarchical Bayesian Approach,
RS(11), No. 9, 2019, pp. xx-yy.
DOI Link 1905
BibRef

Tian, J.Y.[Jin-Yan], Wang, L.[Le], Li, X.J.[Xiao-Juan], Yin, D.[Dameng], Gong, H.[Huili], Nie, S.[Sheng], Shi, C.[Chen], Zhong, R.[Ruofei], Liu, X.M.[Xiao-Meng], Xu, R.[Ronglong],
Canopy Height Layering Biomass Estimation Model (CHL-BEM) with Full-Waveform LiDAR,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Zhang, L.J.[Lin-Jing], Shao, Z.F.[Zhen-Feng], Liu, J.C.[Jian-Chen], Cheng, Q.M.[Qi-Min],
Deep Learning Based Retrieval of Forest Aboveground Biomass from Combined LiDAR and Landsat 8 Data,
RS(11), No. 12, 2019, pp. xx-yy.
DOI Link 1907
BibRef

Li, S.[Siqi], Quackenbush, L.J.[Lindi J.], Im, J.[Jungho],
Airborne Lidar Sampling Strategies to Enhance Forest Aboveground Biomass Estimation from Landsat Imagery,
RS(11), No. 16, 2019, pp. xx-yy.
DOI Link 1909
BibRef

Zhang, X.[Xueyan],
Quick Aboveground Carbon Stock Estimation of Densely Planted Shrubs by Using Point Cloud Derived from Unmanned Aerial Vehicle,
RS(11), No. 24, 2019, pp. xx-yy.
DOI Link 1912
BibRef

Marczak, P.T.[Paulina T.], van Ewijk, K.Y.[Karin Y.], Treitz, P.M.[Paul M.], Scott, N.A.[Neal A.], Robinson, D.C.E.[Donald C.E.],
Predicting Carbon Accumulation in Temperate Forests of Ontario, Canada Using a LiDAR-Initialized Growth-and-Yield Model,
RS(12), No. 1, 2020, pp. xx-yy.
DOI Link 2001
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Xie, B.[Bo], Cao, C.[Chunxiang], Xu, M.[Min], Bashir, B.[Barjeece], Singh, R.P.[Ramesh P.], Huang, Z.B.[Zhi-Bin], Lin, X.J.[Xiao-Juan],
Regional Forest Volume Estimation by Expanding LiDAR Samples Using Multi-Sensor Satellite Data,
RS(12), No. 3, 2020, pp. xx-yy.
DOI Link 2002
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Jiang, X.[Xiandie], Li, G.[Guiying], Lu, D.S.[Deng-Sheng], Chen, E.[Erxue], Wei, X.[Xinliang],
Stratification-Based Forest Aboveground Biomass Estimation in a Subtropical Region Using Airborne Lidar Data,
RS(12), No. 7, 2020, pp. xx-yy.
DOI Link 2004
BibRef

Kuželka, K.[Karel], Slavík, M.[Martin], Surový, P.[Peter],
Very High Density Point Clouds from UAV Laser Scanning for Automatic Tree Stem Detection and Direct Diameter Measurement,
RS(12), No. 8, 2020, pp. xx-yy.
DOI Link 2004
BibRef

da Silva, V.S.[Vanessa Sousa], Silva, C.A.[Carlos Alberto], Mohan, M.[Midhun], Cardil, A.[Adrián], Rex, F.E.[Franciel Eduardo], Loureiro, G.H.[Gabrielle Hambrecht], Alves de Almeida, D.R.[Danilo Roberti], Broadbent, E.N.[Eben North], Gorgens, E.B.[Eric Bastos], Corte, A.P.D.[Ana Paula Dalla], Silva, E.A.[Emanuel Araújo], Valbuena, R.[Rubén], Klauberg, C.[Carine],
Combined Impact of Sample Size and Modeling Approaches for Predicting Stem Volume in Eucalyptus spp. Forest Plantations Using Field and LiDAR Data,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
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Leite, R.V.[Rodrigo Vieira], do Amaral, C.H.[Cibele Hummel], de Paula Pires, R.[Raul], Silva, C.A.[Carlos Alberto], Soares, C.P.B.[Carlos Pedro Boechat], Macedo, R.P.[Renata Paulo], Lopes da Silva, A.A.[Antonilmar Araújo], Broadbent, E.N.[Eben North], Mohan, M.[Midhun], Leite, H.G.[Hélio Garcia],
Estimating Stem Volume in Eucalyptus Plantations Using Airborne LiDAR: A Comparison of Area- and Individual Tree-Based Approaches,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
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Rex, F.E.[Franciel Eduardo], Silva, C.A.[Carlos Alberto], Corte, A.P.D.[Ana Paula Dalla], Klauberg, C.[Carine], Mohan, M.[Midhun], Cardil, A.[Adrián], da Silva, V.S.[Vanessa Sousa], Alves de Almeida, D.R.[Danilo Roberti], Garcia, M.[Mariano], Broadbent, E.N.[Eben North], Valbuena, R.[Ruben], Stoddart, J.[Jaz], Merrick, T.[Trina], Hudak, A.T.[Andrew Thomas],
Comparison of Statistical Modelling Approaches for Estimating Tropical Forest Aboveground Biomass Stock and Reporting Their Changes in Low-Intensity Logging Areas Using Multi-Temporal LiDAR Data,
RS(12), No. 9, 2020, pp. xx-yy.
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Sagang, L.T.[Le_Bienfaiteur T.], Ploton, P.[Pierre], Sonké, B.[Bonaventure], Poilvé, H.[Hervé], Couteron, P.[Pierre], Barbier, N.[Nicolas],
Airborne Lidar Sampling Pivotal for Accurate Regional AGB Predictions from Multispectral Images in Forest-Savanna Landscapes,
RS(12), No. 10, 2020, pp. xx-yy.
DOI Link 2006
Above-Ground-Biomass. BibRef

d'Oliveira, M.V.N.[Marcus V. N.], Broadbent, E.N.[Eben N.], Oliveira, L.C.[Luis C.], Almeida, D.R.A.[Danilo R. A.], Papa, D.A.[Daniel A.], Ferreira, M.E.[Manuel E.], Zambrano, A.M.A.[Angelica M. Almeyda], Silva, C.A.[Carlos A.], Avino, F.S.[Felipe S.], Prata, G.A.[Gabriel A.], Mello, R.A.[Ricardo A.], Figueiredo, E.O.[Evandro O.], de Castro Jorge, L.A.[Lúcio A.], Junior, L.[Leomar], Albuquerque, R.W.[Rafael W.], Brancalion, P.H.S.[Pedro H. S.], Wilkinson, B.[Ben], Oliveira-da-Costa, M.[Marcelo],
Aboveground Biomass Estimation in Amazonian Tropical Forests: a Comparison of Aircraft- and GatorEye UAV-borne LiDAR Data in the Chico Mendes Extractive Reserve in Acre, Brazil,
RS(12), No. 11, 2020, pp. xx-yy.
DOI Link 2006
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Windrim, L.[Lloyd], Bryson, M.[Mitch],
Detection, Segmentation, and Model Fitting of Individual Tree Stems from Airborne Laser Scanning of Forests Using Deep Learning,
RS(12), No. 9, 2020, pp. xx-yy.
DOI Link 2005
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Jiang, X.[Xiandie], Li, G.[Guiying], Lu, D.S.[Deng-Sheng], Moran, E.[Emilio], Batistella, M.[Mateus],
Modeling Forest Aboveground Carbon Density in the Brazilian Amazon with Integration of MODIS and Airborne LiDAR Data,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
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Maesano, M.[Mauro], Khoury, S.[Sacha], Nakhle, F.[Farid], Firrincieli, A.[Andrea], Gay, A.[Alan], Tauro, F.[Flavia], Harfouche, A.[Antoine],
UAV-Based LiDAR for High-Throughput Determination of Plant Height and Above-Ground Biomass of the Bioenergy Grass Arundo donax,
RS(12), No. 20, 2020, pp. xx-yy.
DOI Link 2010
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Stefanidou, A.[Alexandra], Gitas, I.Z.[Ioannis Z.], Korhonen, L.[Lauri], Georgopoulos, N.[Nikos], Stavrakoudis, D.[Dimitris],
Multispectral LiDAR-Based Estimation of Surface Fuel Load in a Dense Coniferous Forest,
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DOI Link 2010
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Almeida, A.[André], Gonçalves, F.[Fabio], Silva, G.[Gilson], Souza, R.[Rodolfo], Treuhaft, R.[Robert], Santos, W.[Weslei], Loureiro, D.[Diego], Fernandes, M.[Márcia],
Estimating Structure and Biomass of a Secondary Atlantic Forest in Brazil Using Fourier Transforms of Vertical Profiles Derived from UAV Photogrammetry Point Clouds,
RS(12), No. 21, 2020, pp. xx-yy.
DOI Link 2011
BibRef

Loh, H.Y.[Ho Yan], James, D.[Daniel], Ioki, K.[Keiko], Wong, W.V.C.[Wilson Vun Chiong], Tsuyuki, S.[Satoshi], Phua, M.H.[Mui-How],
Aboveground Biomass Changes in Tropical Montane Forest of Northern Borneo Estimated Using Spaceborne and Airborne Digital Elevation Data,
RS(12), No. 22, 2020, pp. xx-yy.
DOI Link 2011
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Büyüksalih, I., Bayburt, S., Schardt, M., Büyüksalih, G.,
Forest Stem Volume Calculation Using Airborne Lidar Data,
Hannover17(265-270).
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Yilmaz, V., Serifoglu, C., Gungor, O.,
Determining Stand Parameters From Uas-based Point Clouds,
ISPRS16(B1: 413-416).
DOI Link 1610
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Hadas, E., Borkowski, A., Estornell, J.,
Algorithm For The Automatic Estimation Of Agricultural Tree Geometric Parameters Using Airborne Laser Scanning Data,
ISPRS16(B8: 629-632).
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Chen, G.[Gang], Hay, G.[Geoffrey],
Using support vector regression and segmentation to estimate forest height, biomass and volume from LiDAR transects and Quickbird imagery,
CGC10(112).
PDF File. 1006
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Andersen, H.E., Breidenbach, J.,
Statistical Properties of Mean Stand Biomass Estimators in a Lidar-Based Double Sampling Forest Survey Design,
Laser07(8).
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Breidenbach, J., McGaughey, R., Andersen, H.E., Kändler, G., Reutebuch, S.,
A Mixed Effects Model to Estimate Stand Volume by Means of Small Footprint Airborne Lidar Data for an American and German Study Site,
Laser07(77).
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Stephens, P.R., Watt, P.J., Loubser, D., Haywood, A., Kimberley, M.O.,
Estimation of Carbon Stocks in New Zealand Planted Forests Using Airborne Scanning Lidar,
Laser07(389).
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Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Biomass Measurements, Forest, Terrestial Laser Techniques .


Last update:Nov 23, 2020 at 10:27:11