22.5.9.3 Trees, Forest, Stem Volume, Biomass Measurements

Chapter Contents (Back)
Stem Volume. Forest. Biomass Measurement. See also Biomass Measurements for Individual Trees. More for the tops than totally biomass: See also Trees, Forest Canopy Analysis.

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

Pekkarinen, A.,
A method for the segmentation of very high spatial resolution images of forested landscapes,
JRS(23), No. 14, July 2002, pp. 2817-2836. 0208
BibRef

Pekkarinen, A.[Anssi],
Image segment-based spectral features in the estimation of timber volume,
RSE(82), No. 2-3, October 2002, pp. 349-359.
HTML Version. 0210
BibRef

Askne, J., Santoro, M.,
Automatic Model-Based Estimation of Boreal Forest Stem Volume From Repeat Pass C-band InSAR Coherence,
GeoRS(47), No. 2, February 2009, pp. 513-516.
IEEE DOI 0903
See also Multitemporal Repeat Pass SAR Interferometry of Boreal Forests. BibRef

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

Norjamäki, I., Tokola, T.,
Comparison of Atmospheric Correction Methods in Mapping Timber Volume with Multitemporal Landsat Images in Kainuu, Finland,
PhEngRS(73), No. 2, February 2007, pp. 155-164.
WWW Link. 0704
The estimation of forest characteristics from an atmospherically corrected Landsat EMT+ mosaic. BibRef

Saatchi, S., Halligan, K.Q., Despain, D.G., Crabtree, R.L.,
Estimation of Forest Fuel Load From Radar Remote Sensing,
GeoRS(45), No. 6, June 2007, pp. 1726-1740.
IEEE DOI 0706
BibRef

Hallberg, B., Smith-Jonforsen, G., Ulander, L.M.H., Sandberg, G.,
A Physical-Optics Model for Double-Bounce Scattering From Tree Stems Standing on an Undulating Ground Surface,
GeoRS(46), No. 9, September 2008, pp. 2607-2621.
IEEE DOI 0810
BibRef

Folkesson, K., Smith-Jonforsen, G., Ulander, L.M.H.,
Model-Based Compensation of Topographic Effects for Improved Stem-Volume Retrieval From CARABAS-II VHF-Band SAR Images,
GeoRS(47), No. 4, April 2009, pp. 1045-1055.
IEEE DOI 0903
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

Amini, J., Sumantyo, J.T.S.,
Employing a Method on SAR and Optical Images for Forest Biomass Estimation,
GeoRS(47), No. 12, December 2009, pp. 4020-4026.
IEEE DOI 0912
BibRef

Li, H.[Hui], Mausel, P.[Paul], Brondizio, E.[Eduardo], Deardorff, D.[David],
A framework for creating and validating a non-linear spectrum-biomass model to estimate the secondary succession biomass in moist tropical forests,
PandRS(65), No. 2, March 2010, pp. 241-254.
Elsevier DOI 1003
Remote sensing; Amazonian forest; Landsat; Modeling; SWIR 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

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

Gama, F., Dos Santos, J.R., Mura, J.C.,
Eucalyptus Biomass and Volume Estimation Using Interferometric and Polarimetric SAR Data,
RS(2), No. 4, April 2010, pp. 939-956.
DOI Link 1203
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

Liang, X.L.[Xin-Lian], Litkey, P.[Paula], Hyyppä, J.[Juha], Kaartinen, H.[Harri], Vastaranta, M.[Mikko], Holopainen, M.[Markus],
Automatic Stem Mapping Using Single-Scan Terrestrial Laser Scanning,
GeoRS(50), No. 2, February 2012, pp. 661-670.
IEEE DOI 1201
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., Hyyppä, J., Yu, X., Liang, X.L.[Xin-Lian], Matikainen, L., Karila, K., Litkey, P., 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

Liang, X.L.[Xin-Lian], Kankare, V., Yu, X.W.[Xiao-Wei], Hyyppa, J., Holopainen, M.,
Automated Stem Curve Measurement Using Terrestrial Laser Scanning,
GeoRS(52), No. 3, March 2014, pp. 1739-1748.
IEEE DOI 1403
calibration BibRef

Liang, X., Hyyppä, J., Kaartinen, H., Holopainen, M., Melkas, T.,
Detecting Changes in Forest Structure over Time with Bi-Temporal Terrestrial Laser Scanning Data,
IJGI(1), No. 3, 2012, pp. 242-255.
DOI Link 1211
BibRef

Kaasalainen, S.[Sanna], Krooks, A.[Anssi], Liski, J.[Jari], Raumonen, P.[Pasi], Kaartinen, H.[Harri], Kaasalainen, M.[Mikko], Puttonen, E.[Eetu], Anttila, K.[Kati], Mäkipää, R.[Raisa],
Change Detection of Tree Biomass with Terrestrial Laser Scanning and Quantitative Structure Modelling,
RS(6), No. 5, 2014, pp. 3906-3922.
DOI Link 1407
BibRef

Puttonen, E., Lehtomäki, M., Kaartinen, H., Zhu, L., Kukko, A., Jaakkola, A.,
Improved Sampling for Terrestrial and Mobile Laser Scanner Point Cloud Data,
RS(5), No. 4, April 2013, pp. 1754-1773.
DOI Link 1305
BibRef

Neumann, M., Saatchi, S.S., Ulander, L.M.H., Fransson, J.E.S.,
Assessing Performance of L- and P-Band Polarimetric Interferometric SAR Data in Estimating Boreal Forest Above-Ground Biomass,
GeoRS(50), No. 3, March 2012, pp. 714-726.
IEEE DOI 1203
BibRef

Ballhorn, U., Jubanski, J.[Juilson], Siegert, F.[Florian],
ICESat/GLAS Data as a Measurement Tool for Peatland Topography and Peat Swamp Forest Biomass in Kalimantan, Indonesia,
RS(3), No. 9, September 2011, pp. 1957-1982.
DOI Link 1203
BibRef

Englhart, S.[Sandra], Jubanski, J.[Juilson], Siegert, F.[Florian],
Quantifying Dynamics in Tropical Peat Swamp Forest Biomass with Multi-Temporal LiDAR Datasets,
RS(5), No. 5, 2013, pp. 2368-2388.
DOI Link 1307
BibRef

Tsui, O.W.[Olivier W.], Coops, N.C.[Nicholas C.], Wulder, M.A.[Michael A.], Marshall, P.L.[Peter L.], McCardle, A.[Adrian],
Using multi-frequency radar and discrete-return LiDAR measurements to estimate above-ground biomass and biomass components in a coastal temperate forest,
PandRS(69), No. 1, April 2012, pp. 121-133.
Elsevier DOI 1202
Above-ground biomass; Radar; LiDAR; Coherence; Polarimetry; Temperate forests BibRef

Sarker, M.L.R.[M. Latifur Rahman], Nichol, J.[Janet], Ahmad, B.[Baharin], Busu, I.[Ibrahim], Rahman, A.A.[Alias Abdul],
Potential of texture measurements of two-date dual polarization PALSAR data for the improvement of forest biomass estimation,
PandRS(69), No. 1, April 2012, pp. 146-166.
Elsevier DOI 1202
PALSAR; Dual polarization; SAR image texture; Saturation level; Forest biomass; Leave-One-Out Cross-Validation BibRef

Eckert, S.,
Improved Forest Biomass and Carbon Estimations Using Texture Measures from WorldView-2 Satellite Data,
RS(4), No. 4, April 2012, pp. 810-829.
DOI Link 1202
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

Anderson, L.,
Biome-Scale Forest Properties in Amazonia Based on Field and Satellite Observations,
RS(4), No. 5, May 2012, pp. 1245-1271.
DOI Link 1205
BibRef

Cutler, M.E.J., Boyd, D.S., Foody, G.M., Vetrivel, A.,
Estimating tropical forest biomass with a combination of SAR image texture and Landsat TM data: An assessment of predictions between regions,
PandRS(70), No. 1, June 2012, pp. 66-77.
Elsevier DOI 1206
Biomass; SAR; Artificial neural network; Wavelets; Allometry 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

Wijedasa, L., Sloan, S., Michelakis, D., Clements, G.,
Overcoming Limitations with Landsat Imagery for Mapping of Peat Swamp Forests in Sundaland,
RS(4), No. 9, September 2012, pp. 2595-2618.
DOI 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

le Maire, G., Marsden, C., Nouvellon, Y., Stape, J., Ponzoni, F.,
Calibration of a Species-Specific Spectral Vegetation Index for Leaf Area Index (LAI) Monitoring: Example with MODIS Reflectance Time-Series on Eucalyptus Plantations,
RS(4), No. 12, December 2012, pp. 3766-3780.
DOI Link 1211
BibRef

Muinonen, E., Parikka, H., Pokharel, Y., Shrestha, S., Eerikäinen, K.,
Utilizing a Multi-Source Forest Inventory Technique, MODIS Data and Landsat TM Images in the Production of Forest Cover and Volume Maps for the Terai Physiographic Zone in Nepal,
RS(4), No. 12, December 2012, pp. 3920-3947.
DOI Link 1211
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

Ghasemi, N., Sahebi, M.R., Mohammadzadeh, A.,
Biomass Estimation of a Temperate Deciduous Forest Using Wavelet Analysis,
GeoRS(51), No. 2, February 2013, pp. 765-776.
IEEE DOI 1302
BibRef

Raumonen, P.[Pasi], Kaasalainen, M.[Mikko], Åkerblom, M., Kaasalainen, S.[Sanna], Kaartinen, H.[Harri], Vastaranta, M., Holopainen, M., Disney, M.I., Lewis, P.E.,
Fast Automatic Precision Tree Models from Terrestrial Laser Scanner Data,
RS(5), No. 2, February 2013, pp. 491-520.
DOI Link 1303
See also Algorithm for Automatic Road Asphalt Edge Delineation from Mobile Laser Scanner Data Using the Line Clouds Concept, An. BibRef

Raumonen, P.[Pasi], Kaasalainen, S.[Sanna], Kaasalainen, M.[Mikko], Kaartinen, H.[Harri],
Approximation of Volume and Branch Size Distribution of Trees from Laser Scanner Data,
Laser11(xx-yy).
DOI Link 1109
BibRef

Pueschel, P.[Pyare], Newnham, G.[Glenn], Rock, G.[Gilles], Udelhoven, T.[Thomas], Werner, W.[Willy], Hill, J.[Joachim],
The influence of scan mode and circle fitting on tree stem detection, stem diameter and volume extraction from terrestrial laser scans,
PandRS(77), No. 1, March 2013, pp. 44-56.
Elsevier DOI 1303
Terrestrial laser scanning (TLS); Forest inventory; Stem detection; Stem diameter; Stem volume BibRef

Casady, G., van Leeuwen, W., Reed, B.,
Estimating Winter Annual Biomass in the Sonoran and Mojave Deserts with Satellite- and Ground-Based Observations,
RS(5), No. 2, February 2013, pp. 909-926.
DOI Link 1303
BibRef

Pueschel, P.[Pyare],
The influence of scanner parameters on the extraction of tree metrics from FARO Photon 120 terrestrial laser scans,
PandRS(78), No. 1, April 2013, pp. 58-68.
Elsevier DOI 1304
Phase-shift scanner; Forest inventory; Stem detection; Stem diameter; Stem volume BibRef

Robinson, C., Saatchi, S., Neumann, M., Gillespie, T.,
Impacts of Spatial Variability on Aboveground Biomass Estimation from L-Band Radar in a Temperate Forest,
RS(5), No. 3, March 2013, pp. 1001-1023.
DOI Link 1304
BibRef

Carreiras, J., Melo, J., Vasconcelos, M.,
Estimating the Above-Ground Biomass in Miombo Savanna Woodlands (Mozambique, East Africa) Using L-Band Synthetic Aperture Radar Data,
RS(5), No. 4, April 2013, pp. 1524-1548.
DOI Link 1305
BibRef

Ahmed, R.[Razi], Siqueira, P.[Paul], Hensley, S.[Scott], Bergen, K.[Kathleen],
Uncertainty of Forest Biomass Estimates in North Temperate Forests Due to Allometry: Implications for Remote Sensing,
RS(5), No. 6, 2013, pp. 3007-3036.
DOI Link 1307
BibRef

Ahmed, R.[Razi], Siqueira, P.[Paul], Hensley, S.[Scott],
Analyzing the Uncertainty of Biomass Estimates From L-Band Radar Backscatter Over the Harvard and Howland Forests,
GeoRS(52), No. 6, June 2014, pp. 3568-3586.
IEEE DOI 1403
Backscatter 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

Cui, X.H.[Xi-Hong], Guo, L.[Li], Chen, J.[Jin], Chen, X.H.[Xue-Hong], Zhu, X.L.[Xiao-Lin],
Estimating Tree-Root Biomass in Different Depths Using Ground-Penetrating Radar: Evidence from a Controlled Experiment,
GeoRS(51), No. 6, 2013, pp. 3410-3423.
IEEE DOI ground-penetrating radar; metal reflector experiment; root biomass after attenuation-effect compensation; soil water content 1307
BibRef

Sarker, M.L.R., Nichol, J., Iz, H.B., Ahmad, B.B., Rahman, A.A.,
Forest Biomass Estimation Using Texture Measurements of High-Resolution Dual-Polarization C-Band SAR Data,
GeoRS(51), No. 6, 2013, pp. 3371-3384.
IEEE DOI 1307
SAR signatures; carbon storage estimation; texture measurement; texture ratio BibRef

Jung, J.[Jaehoon], Kim, S.[Sangpil], Hong, S.[Sungchul], Kim, K.M.[Kyoung-Min], Kim, E.[Eunsook], Im, J.H.[Jung-Ho], Heo, J.[Joon],
Effects of national forest inventory plot location error on forest carbon stock estimation using k-nearest neighbor algorithm,
PandRS(81), No. 1, July 2013, pp. 82-92.
Elsevier DOI 1306
Forest carbon stock; National forest inventory; k-Nearest neighbor; Uncertainty; Plot location error BibRef

Sow, M.[Momadou], Mbow, C.[Cheikh], Hély, C.[Christelle], Fensholt, R.[Rasmus], Sambou, B.[Bienvenu],
Estimation of Herbaceous Fuel Moisture Content Using Vegetation Indices and Land Surface Temperature from MODIS Data,
RS(5), No. 6, 2013, pp. 2617-2638.
DOI Link 1307
BibRef

Minh, D.H.T.[Dinh Ho Tong], Tebaldini, S., Rocca, F., Koleck, T., Borderies, P., Albinet, C., Villard, L., Hamadi, A., Le Toan, T.,
Ground-Based Array for Tomographic Imaging of the Tropical Forest in P-Band,
GeoRS(51), No. 8, 2013, pp. 4460-4472.
IEEE DOI 1307
Array design BibRef

Hamadi, A., Albinet, C., Borderies, P., Koleck, T., Villard, L., Minh, D.H.T.[Dinh Ho Tong], Le Toan, T.,
Temporal Survey of Polarimetric P-Band Scattering of Tropical Forests,
GeoRS(52), No. 8, August 2014, pp. 4539-4547.
IEEE DOI 1403
Antennas BibRef

Suchenwirth, L.[Leonhard], Förster, M.[Michael], Lang, F.[Friederike], Kleinschmit, B.[Birgit],
Estimation and Mapping of Carbon Stocks in Riparian Forests by using a Machine Learning Approach with Multiple Geodata,
PFG(2013), No. 4, 2013, pp. 333-349.
DOI Link 1309
BibRef

Santoro, M.[Maurizio], Cartus, O.[Oliver], Fransson, J.E.S.[Johan E.S.], Shvidenko, A.[Anatoly], McCallum, I.[Ian], Hall, R.J.[Ronald J.], Beaudoin, A.[André], Beer, C.[Christian], Schmullius, C.[Christiane],
Estimates of Forest Growing Stock Volume for Sweden, Central Siberia, and Québec Using Envisat Advanced Synthetic Aperture Radar Backscatter Data,
RS(5), No. 9, 2013, pp. 4503-4532.
DOI Link 1310
BibRef

Chávez, R.O.[Roberto O.], Clevers, J.G.P.W.[Jan G. P. W.], Herold, M.[Martin], Acevedo, E.[Edmundo], Ortiz, M.[Mauricio],
Assessing Water Stress of Desert Tamarugo Trees Using in situ Data and Very High Spatial Resolution Remote Sensing,
RS(5), No. 10, 2013, pp. 5064-5088.
DOI Link 1311
BibRef

Ringdahl, O.[Ola], Hohnloser, P.[Peter], Hellström, T.[Thomas], Holmgren, J.[Johan], Lindroos, O.[Ola],
Enhanced Algorithms for Estimating Tree Trunk Diameter Using 2D Laser Scanner,
RS(5), No. 10, 2013, pp. 4839-4856.
DOI Link 1311
BibRef

Aguilera, E., Nannini, M., Reigber, A.,
Wavelet-Based Compressed Sensing for SAR Tomography of Forested Areas,
GeoRS(51), No. 12, 2013, pp. 5283-5295.
IEEE DOI 1312
remote sensing by radar BibRef

Askne, J.I.H.[Jan I.H.], Fransson, J.E.S.[Johan E.S.], Santoro, M.[Maurizio], Soja, M.J.[Maciej J.], Ulander, L.M.H.[Lars M.H.],
Model-Based Biomass Estimation of a Hemi-Boreal Forest from Multitemporal TanDEM-X Acquisitions,
RS(5), No. 11, 2013, pp. 5574-5597.
DOI Link 1312
BibRef

Chowdhury, T.A.[Tanvir Ahmed], Thiel, C.[Christian], Schmullius, C.[Christiane], Stelmaszczuk-Górska, M.[Martyna],
Polarimetric Parameters for Growing Stock Volume Estimation Using ALOS PALSAR L-Band Data over Siberian Forests,
RS(5), No. 11, 2013, pp. 5725-5756.
DOI Link 1312
BibRef

Thiel, C.[Christian], Schmullius, C.[Christiane],
Impact of Tree Species on Magnitude of PALSAR Interferometric Coherence over Siberian Forest at Frozen and Unfrozen Conditions,
RS(6), No. 2, 2014, pp. 1124-1136.
DOI Link 1403
BibRef

d'Alessandro, M.M., Tebaldini, S., Rocca, F.,
Phenomenology of Ground Scattering in a Tropical Forest Through Polarimetric Synthetic Aperture Radar Tomography,
GeoRS(51), No. 8, 2013, pp. 4430-4437.
IEEE DOI 1307
Histograms BibRef

Minh, D.H.T.[Dinh Ho Tong], Toan, T.L.[Thuy Le], Rocca, F., Tebaldini, S., d'Alessandro, M.M., Villard, L.,
Relating P-Band Synthetic Aperture Radar Tomography to Tropical Forest Biomass,
GeoRS(52), No. 2, February 2014, pp. 967-979.
IEEE DOI 1402
geophysical image processing BibRef

Minh, D.H.T.[Dinh Ho Tong], Tebaldini, S., Rocca, F., Toan, T.L.[Thuy Le], Villard, L., Dubois-Fernandez, P.C.,
Capabilities of BIOMASS Tomography for Investigating Tropical Forests,
GeoRS(53), No. 2, February 2015, pp. 965-975.
IEEE DOI 1411
geometry BibRef

Vastaranta, M., Holopainen, M., Karjalainen, M., Kankare, V., Hyyppa, J., Kaasalainen, S.,
TerraSAR-X Stereo Radargrammetry and Airborne Scanning LiDAR Height Metrics in Imputation of Forest Aboveground Biomass and Stem Volume,
GeoRS(52), No. 2, February 2014, pp. 1197-1204.
IEEE DOI 1402
geophysical techniques BibRef

Vastaranta, M.[Mikko], Niemi, M.[Mikko], Karjalainen, M.[Mika], Peuhkurinen, J.[Jussi], Kankare, V.[Ville], Hyyppä, J.[Juha], Holopainen, M.[Markus],
Prediction of Forest Stand Attributes Using TerraSAR-X Stereo Imagery,
RS(6), No. 4, 2014, pp. 3227-3246.
DOI Link 1405
BibRef

Barbosa, J.M.[Jomar Magalhães], Melendez-Pastor, I.[Ignacio], Navarro-Pedreño, J.[Jose], Bitencourt, M.D.[Marisa Dantas],
Remotely sensed biomass over steep slopes: An evaluation among successional stands of the Atlantic Forest, Brazil,
PandRS(88), No. 1, 2014, pp. 91-100.
Elsevier DOI 1402
Aboveground biomass BibRef

Olsoy, P.J.[Peter J.], Glenn, N.F.[Nancy F.], Clark, P.E.[Patrick E.], Derryberry, D.R.[DeWayne R.],
Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning,
PandRS(88), No. 1, 2014, pp. 166-173.
Elsevier DOI 1402
Terrestrial LiDAR 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
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And: Correction: RS(7), No. 8, 2015, pp. 10242.
DOI Link 1509
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van Beek, J.[Jonathan], Tits, L.[Laurent], Somers, B.[Ben], Coppin, P.[Pol],
Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery,
RS(5), No. 12, 2013, pp. 6647-6666.
DOI Link 1402
Corrections: See also Correction: Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery. BibRef

van Beek, J.[Jonathan], Tits, L.[Laurent], Somers, B.[Ben], Janssens, P.[Pieter], Odeurs, W.[Wendy], Vandendriessche, H.[Hilde], Deckers, T.[Tom], Coppin, P.[Pol],
Correction: Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery,
RS(6), No. 2, 2014, pp. 1760-1761.
DOI Link 1403
See also Stem Water Potential Monitoring in Pear Orchards through WorldView-2 Multispectral Imagery. BibRef

van Beek, J.[Jonathan], Tits, L.[Laurent], Somers, B.[Ben], Deckers, T.[Tom], Verjans, W.[Wim], Bylemans, D.[Dany], Janssens, P.[Pieter], Coppin, P.[Pol],
Temporal Dependency of Yield and Quality Estimation through Spectral Vegetation Indices in Pear Orchards,
RS(7), No. 8, 2015, pp. 9886.
DOI Link 1509
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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

Tanase, M.A., Panciera, R., Lowell, K., Tian, S., Garcia-Martin, A., Walker, J.P.,
Sensitivity of L-Band Radar Backscatter to Forest Biomass in Semiarid Environments: A Comparative Analysis of Parametric and Nonparametric Models,
GeoRS(52), No. 8, August 2014, pp. 4671-4685.
IEEE DOI 1403
Backscatter BibRef

Hensley, S., Oveisgharan, S., Saatchi, S., Simard, M., Ahmed, R., Haddad, Z.,
An Error Model for Biomass Estimates Derived From Polarimetric Radar Backscatter,
GeoRS(52), No. 7, July 2014, pp. 4065-4082.
IEEE DOI 1403
Backscatter BibRef

Rogers, N.C., Quegan, S., Kim, J.S.[Jun Su], Papathanassiou, K.P.,
Impacts of Ionospheric Scintillation on the BIOMASS P-Band Satellite SAR,
GeoRS(52), No. 3, March 2014, pp. 1856-1868.
IEEE DOI 1403
radar polarimetry BibRef

Kim, J.S.[Jun Su], Papathanassiou, K.P., Scheiber, R., Quegan, S.,
Correcting Distortion of Polarimetric SAR Data Induced by Ionospheric Scintillation,
GeoRS(53), No. 12, December 2015, pp. 6319-6335.
IEEE DOI 1512
Faraday effect BibRef

Mustafa, Y.T., Tolpekin, V.A., Stein, A.,
Improvement of Spatio-temporal Growth Estimates in Heterogeneous Forests Using Gaussian Bayesian Networks,
GeoRS(52), No. 8, August 2014, pp. 4980-4991.
IEEE DOI 1403
Data models BibRef

Persson, H.J.[Henrik J.], Fransson, J.E.S.[Johan E.S.],
Forest Variable Estimation Using Radargrammetric Processing of TerraSAR-X Images in Boreal Forests,
RS(6), No. 3, 2014, pp. 2084-2107.
DOI Link 1404
BibRef

Soja, M.J., Persson, H.J., Ulander, L.M.H.,
Estimation of Forest Biomass From Two-Level Model Inversion of Single-Pass InSAR Data,
GeoRS(53), No. 9, September 2015, pp. 5083-5099.
IEEE DOI 1506
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And: Corrections: GeoRS(53), No. 10, October 2015, pp. 5795-5795.
IEEE DOI 1509
Biological system modeling BibRef

Persson, H.J.[Henrik J.],
Estimation of Boreal Forest Attributes from Very High Resolution Pléiades Data,
RS(8), No. 9, 2016, pp. 736.
DOI Link 1610
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Calvert, K.[Kirby], Mabee, W.[Warren],
Spatial Analysis of Biomass Resources within a Socio-Ecologically Heterogeneous Region: Identifying Opportunities for a Mixed Feedstock Stream,
IJGI(3), No. 1, 2014, pp. 209-232.
DOI Link 1404
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Frazier, R.J.[Ryan J.], Coops, N.C.[Nicholas C.], Wulder, M.A.[Michael A.], Kennedy, R.[Robert],
Characterization of aboveground biomass in an unmanaged boreal forest using Landsat temporal segmentation metrics,
PandRS(92), No. 1, 2014, pp. 137-146.
Elsevier DOI 1407
Landsat BibRef

Gómez, C.[Cristina], White, J.C.[Joanne C.], Wulder, M.A.[Michael A.], Alejandro, P.[Pablo],
Historical forest biomass dynamics modelled with Landsat spectral trajectories,
PandRS(93), No. 1, 2014, pp. 14-28.
Elsevier DOI 1407
Remote sensing 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

Attarchi, S.[Sara], Gloaguen, R.[Richard],
Improving the Estimation of Above Ground Biomass Using Dual Polarimetric PALSAR and ETM+ Data in the Hyrcanian Mountain Forest (Iran),
RS(6), No. 5, 2014, pp. 3693-3715.
DOI Link 1407
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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
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Zhu, S.P.[Shi-Ping], Huang, C.L.[Chun-Lin], Su, Y.[Yi], Sato, M.[Motoyuki],
3D Ground Penetrating Radar to Detect Tree Roots and Estimate Root Biomass in the Field,
RS(6), No. 6, 2014, pp. 5754-5773.
DOI Link 1407
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Cartus, O.[Oliver], Kellndorfer, J.[Josef], Walker, W.[Wayne], Franco, C.[Carol], Bishop, J.[Jesse], Santos, L.[Lucio], Fuentes, J.M.M.[José María Michel],
A National, Detailed Map of Forest Aboveground Carbon Stocks in Mexico,
RS(6), No. 6, 2014, pp. 5559-5588.
DOI Link 1407
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Vicharnakorn, P.[Phutchard], Shrestha, R.P.[Rajendra P.], Nagai, M.[Masahiko], Salam, A.P.[Abdul P.], Kiratiprayoon, S.[Somboon],
Carbon Stock Assessment Using Remote Sensing and Forest Inventory Data in Savannakhet, Lao PDR,
RS(6), No. 6, 2014, pp. 5452-5479.
DOI Link 1407
BibRef

Sandberg, G., Ulander, L.M.H., Wallerman, J., Fransson, J.E.S.,
Measurements of Forest Biomass Change Using P-Band Synthetic Aperture Radar Backscatter,
GeoRS(52), No. 10, October 2014, pp. 6047-6061.
IEEE DOI 1407
Backscatter 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

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

Kelsey, K.C.[Katharine C.], Neff, J.C.[Jason C.],
Estimates of Aboveground Biomass from Texture Analysis of Landsat Imagery,
RS(6), No. 7, 2014, pp. 6407-6422.
DOI Link 1408
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Saremi, H.[Hanieh], Kumar, L.[Lalit], Stone, C.[Christine], Melville, G.[Gavin], Turner, R.[Russell],
Sub-Compartment Variation in Tree Height, Stem Diameter and Stocking in a Pinus radiata D. Don Plantation Examined Using Airborne LiDAR Data,
RS(6), No. 8, 2014, pp. 7592-7609.
DOI Link 1410
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Solberg, S., Riegler, G., Nonin, P.,
Estimating Forest Biomass From TerraSAR-X Stripmap Radargrammetry,
GeoRS(53), No. 1, January 2015, pp. 154-161.
IEEE DOI 1410
digital elevation models 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
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Ni, W.J.[Wen-Jian], Zhang, Z.[Zhiyu], Sun, G.Q.[Guo-Qing], Guo, Z.F.[Zhi-Feng], He, Y.T.[Ya-Ting],
The Penetration Depth Derived from the Synthesis of ALOS/PALSAR InSAR Data and ASTER GDEM for the Mapping of Forest Biomass,
RS(6), No. 8, 2014, pp. 7303-7319.
DOI Link 1410
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Windisch, K.[Katrin], Bronner, G.[Günther], Mansberger, R.[Reinfried], Koukal, T.[Tatjana],
Derivation of Dominant Height and Yield Class of Forest Stands by Means of Airborne Remote Sensing Methods,
PFG(2014), No. 5, 2014, pp. 325-338.
DOI Link 1411
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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
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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
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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
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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
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Motohka, T., Yoshida, T., Shibata, H., Tadono, T., Shimada, M.,
Mapping Aboveground Biomass in Northern Japanese Forests Using the ALOS PRISM Digital Surface Model,
GeoRS(53), No. 4, April 2015, pp. 1683-1691.
IEEE DOI 1502
digital elevation models BibRef

Tanaka, S.[Shinya], Takahashi, T.[Tomoaki], Nishizono, T.[Tomohiro], Kitahara, F.[Fumiaki], Saito, H.[Hideki], Iehara, T.[Toshiro], Kodani, E.[Eiji], Awaya, Y.[Yoshio],
Stand Volume Estimation Using the k-NN Technique Combined with Forest Inventory Data, Satellite Image Data and Additional Feature Variables,
RS(7), No. 1, 2014, pp. 378-394.
DOI Link 1502
BibRef

Zhu, X.L.[Xiao-Lin], Liu, D.[Desheng],
Improving Forest Aboveground Biomass Estimation Using Seasonal Landsat NDVI Time-Series,
PandRS(102), No. 1, 2015, pp. 222-231.
Elsevier DOI 1503
Aboveground biomass See also Accurate Mapping of Forest Types Using Dense Seasonal Landsat Time-Series. 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.[Shengli], 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

Dube, T.[Timothy], Mutanga, O.[Onisimo],
Evaluating the utility of the medium-spatial resolution Landsat 8 multispectral sensor in quantifying aboveground biomass in uMgeni catchment, South Africa,
PandRS(101), No. 1, 2015, pp. 36-46.
Elsevier DOI 1503
Biomass estimation BibRef

Dube, T.[Timothy], Mutanga, O.[Onisimo],
The impact of integrating WorldView-2 sensor and environmental variables in estimating plantation forest species aboveground biomass and carbon stocks in uMgeni Catchment, South Africa,
PandRS(119), No. 1, 2016, pp. 415-425.
Elsevier DOI 1610
Aboveground carbon mapping BibRef

Sousa, A.M.O.[Adélia M.O.], Gonçalves, A.C.[Ana Cristina], Mesquita, P.[Paulo], Marques da Silva, J.R.[José R.],
Biomass estimation with high resolution satellite images: A case study of Quercus rotundifolia,
PandRS(101), No. 1, 2015, pp. 69-79.
Elsevier DOI 1503
Quercus rotundifolia 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, A.[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

Shoshany, M.[Maxim], Karnibad, L.[Lev],
Remote Sensing of Shrubland Drying in the South-East Mediterranean, 1995-2010: Water-Use-Efficiency-Based Mapping of Biomass Change,
RS(7), No. 3, 2015, pp. 2283-2301.
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

Joshi, N.P.[Neha P.], Mitchard, E.T.A.[Edward T. A.], Schumacher, J.[Johannes], Johannsen, V.K.[Vivian K.], Saatchi, S.[Sassan], Fensholt, R.[Rasmus],
L-Band SAR Backscatter Related to Forest Cover, Height and Aboveground Biomass at Multiple Spatial Scales across Denmark,
RS(7), No. 4, 2015, pp. 4442-4472.
DOI Link 1505
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Zandler, H.[Harald], Brenning, A.[Alexander], Samimi, C.[Cyrus],
Potential of Space-Borne Hyperspectral Data for Biomass Quantification in an Arid Environment: Advantages and Limitations,
RS(7), No. 4, 2015, pp. 4565-4580.
DOI Link 1505
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Santoro, M.[Maurizio], Eriksson, L.E.B.[Leif E.B.], Fransson, J.E.S.[Johan E.S.],
Reviewing ALOS PALSAR Backscatter Observations for Stem Volume Retrieval in Swedish Forest,
RS(7), No. 4, 2015, pp. 4290-4317.
DOI Link 1505
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Markku, Å.[Åkerblom], Raumonen, P.[Pasi], Kaasalainen, M.[Mikko], Casella, E.[Eric],
Analysis of Geometric Primitives in Quantitative Structure Models of Tree Stems,
RS(7), No. 4, 2015, pp. 4581-4603.
DOI Link 1505
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Singh, M.[Minerva], Evans, D.[Damian], Friess, D.A.[Daniel A.], Tan, B.S.[Boun Suy], Nin, C.S.[Chan Samean],
Mapping Above-Ground Biomass in a Tropical Forest in Cambodia Using Canopy Textures Derived from Google Earth,
RS(7), No. 5, 2015, pp. 5057-5076.
DOI Link 1506
BibRef

Chi, H.[Hong], Sun, G.Q.[Guo-Qing], Huang, J.L.[Jin-Liang], Guo, Z.F.[Zhi-Feng], Ni, W.J.[Wen-Jian], Fu, A.[Anmin],
National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China,
RS(7), No. 5, 2015, pp. 5534-5564.
DOI Link 1506
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Chi, H.[Hong], Sun, G.Q.[Guo-Qing], Huang, J.L.[Jin-Liang], Li, R.D.[Ren-Dong], Ren, X.Y.[Xian-You], Ni, W.J.[Wen-Jian], Fu, A.[Anmin],
Estimation of Forest Aboveground Biomass in Changbai Mountain Region Using ICESat/GLAS and Landsat/TM Data,
RS(9), No. 7, 2017, pp. xx-yy.
DOI Link 1708
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Quegan, S.[Shaun], Lomas, M.R.,
The Interaction Between Faraday Rotation and System Effects in Synthetic Aperture Radar Measurements of Backscatter and Biomass,
GeoRS(53), No. 8, August 2015, pp. 4299-4312.
IEEE DOI 1506
Faraday effect BibRef

Lavalle, M., Hensley, S.,
Extraction of Structural and Dynamic Properties of Forests From Polarimetric-Interferometric SAR Data Affected by Temporal Decorrelation,
GeoRS(53), No. 9, September 2015, pp. 4752-4767.
IEEE DOI 1506
Biomass 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

Jaskierniak, D.[Dominik], Kuczera, G.[George], Benyon, R.[Richard], Wallace, L.[Luke],
Using Tree Detection Algorithms to Predict Stand Sapwood Area, Basal Area and Stocking Density in Eucalyptus regnans Forest,
RS(7), No. 6, 2015, pp. 7298.
DOI Link 1507
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Huang, W.L.[Wen-Li], Sun, G.Q.[Guo-Qing], Ni, W.J.[Wen-Jian], Zhang, Z.[Zhiyu], Dubayah, R.[Ralph],
Sensitivity of Multi-Source SAR Backscatter to Changes in Forest Aboveground Biomass,
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DOI Link 1509
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Hansen, E.H.[Endre Hofstad], Gobakken, T.[Terje], Solberg, S.[Svein], Kangas, A.[Annika], Ene, L.[Liviu], Mauya, E.[Ernest], Næsset, E.[Erik],
Relative Efficiency of ALS and InSAR for Biomass Estimation in a Tanzanian Rainforest,
RS(7), No. 8, 2015, pp. 9865.
DOI Link 1509
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Karlson, M.[Martin], Ostwald, M.[Madelene], Reese, H.[Heather], Sanou, J.[Josias], Tankoano, B.[Boalidioa], Mattsson, E.[Eskil],
Mapping Tree Canopy Cover and Aboveground Biomass in Sudano-Sahelian Woodlands Using Landsat 8 and Random Forest,
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DOI Link 1509
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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
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Dandois, J.P.[Jonathan P.], Olano, M.[Marc], Ellis, E.C.[Erle C.],
Optimal Altitude, Overlap, and Weather Conditions for Computer Vision UAV Estimates of Forest Structure,
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DOI Link 1511
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Dandois, J.P.[Jonathan P.], Baker, M.[Matthew], Olano, M.[Marc], Parker, G.G.[Geoffrey G.], Ellis, E.C.[Erle C.],
What is the Point? Evaluating the Structure, Color, and Semantic Traits of Computer Vision Point Clouds of Vegetation,
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DOI Link 1705
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Ding, X.K.[Xiao-Kang], Kong, J.[Jianlei], Yan, L.[Lei], Liu, J.[Jinhao], Yu, Z.[Zheng],
A novel stumpage detection method for forest harvesting based on multi-sensor fusion,
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Springer DOI 1511
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Dube, T.[Timothy], Mutanga, O.[Onisimo],
Investigating the robustness of the new Landsat-8 Operational Land Imager derived texture metrics in estimating plantation forest aboveground biomass in resource constrained areas,
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Elsevier DOI 1511
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Blasch, G.[Gerald], Spengler, D.[Daniel], Itzerott, S.[Sibylle], Wessolek, G.[Gerd],
Organic Matter Modeling at the Landscape Scale Based on Multitemporal Soil Pattern Analysis Using RapidEye Data,
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Nink, S.[Sascha], Hill, J.[Joachim], Buddenbaum, H.[Henning], Stoffels, J.[Johannes], Sachtleber, T.[Thomas], Langshausen, J.[Joachim],
Assessing the Suitability of Future Multi- and Hyperspectral Satellite Systems for Mapping the Spatial Distribution of Norway Spruce Timber Volume,
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Rodríguez-Cuenca, B.[Borja], García-Cortés, S.[Silverio], Ordóñez, C.[Celestino], Alonso, M.C.[Maria C.],
Automatic Detection and Classification of Pole-Like Objects in Urban Point Cloud Data Using an Anomaly Detection Algorithm,
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Iizuka, K.[Kotaro], Tateishi, R.[Ryutaro],
Estimation of CO2 Sequestration by the Forests in Japan by Discriminating Precise Tree Age Category using Remote Sensing Techniques,
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Sun, H.[Hua], Qie, G.P.[Guang-Ping], Wang, G.X.[Guang-Xing], Tan, Y.[Yifan], Li, J.P.[Ji-Ping], Peng, Y.[Yougui], Ma, Z.G.[Zhong-Gang], Luo, C.Q.[Chao-Qin],
Increasing the Accuracy of Mapping Urban Forest Carbon Density by Combining Spatial Modeling and Spectral Unmixing Analysis,
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Yu, X.W.[Xiao-Wei], Hyyppä, J.[Juha], Karjalainen, M.[Mika], Nurminen, K.[Kimmo], Karila, K.[Kirsi], Vastaranta, M.[Mikko], Kankare, V.[Ville], Kaartinen, H.[Harri], Holopainen, M.[Markus], Honkavaara, E.[Eija], Kukko, A.[Antero], Jaakkola, A.[Anttoni], Liang, X.L.[Xin-Lian], Wang, Y.S.[Yun-Sheng], Hyyppä, H.[Hannu], Katoh, M.[Masato],
Comparison of Laser and Stereo Optical, SAR and InSAR Point Clouds from Air- and Space-Borne Sources in the Retrieval of Forest Inventory Attributes,
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Sibanda, M.[Mbulisi], Mutanga, O.[Onisimo], Rouget, M.[Mathieu],
Examining the potential of Sentinel-2 MSI spectral resolution in quantifying above ground biomass across different fertilizer treatments,
PandRS(110), No. 1, 2015, pp. 55-65.
Elsevier DOI 1601
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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,
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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,
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Surový, P.[Peter], Yoshimoto, A.[Atsushi], Panagiotidis, D.[Dimitrios],
Accuracy of Reconstruction of the Tree Stem Surface Using Terrestrial Close-Range Photogrammetry,
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Meng, S.[Shili], Pang, Y.[Yong], Zhang, Z.J.[Zhong-Jun], Jia, W.[Wen], Li, Z.Y.[Zeng-Yuan],
Mapping Aboveground Biomass using Texture Indices from Aerial Photos in a Temperate Forest of Northeastern China,
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Xi, X.H.[Xiao-Huan], Han, T.T.[Ting-Ting], Wang, C.[Cheng], Luo, S.[Shezhou], Xia, S.[Shaobo], Pan, F.F.[Fei-Fei],
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Koedsin, W.[Werapong], Intararuang, W.[Wissarut], Ritchie, R.J.[Raymond J.], Huete, A.[Alfredo],
An Integrated Field and Remote Sensing Method for Mapping Seagrass Species, Cover, and Biomass in Southern Thailand,
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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,
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López-Serrano, P.M.[Pablito M.], Corral-Rivas, J.J.[José J.], Díaz-Varela, R.A.[Ramón A.], Álvarez-González, J.G.[Juan G.], López-Sánchez, C.A.[Carlos A.],
Evaluation of Radiometric and Atmospheric Correction Algorithms for Aboveground Forest Biomass Estimation Using Landsat 5 TM Data,
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Garroutte, E.L.[Erica L.], Hansen, A.J.[Andrew J.], Lawrence, R.L.[Rick L.],
Using NDVI and EVI to Map Spatiotemporal Variation in the Biomass and Quality of Forage for Migratory Elk in the Greater Yellowstone Ecosystem,
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Zhao, P.P.[Pan-Pan], Lu, D.S.[Deng-Sheng], Wang, G.X.[Guang-Xing], Wu, C.P.[Chu-Ping], Huang, Y.J.[Yu-Jie], Yu, S.Q.[Shu-Quan],
Examining Spectral Reflectance Saturation in Landsat Imagery and Corresponding Solutions to Improve Forest Aboveground Biomass Estimation,
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Yu, Y.[Yifan], Saatchi, S.[Sassan],
Sensitivity of L-Band SAR Backscatter to Aboveground Biomass of Global Forests,
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Hu, T.[Tianyu], Su, Y.[Yanjun], Xue, B.L.[Bao-Lin], Liu, J.[Jin], Zhao, X.Q.[Xiao-Qian], Fang, J.[Jingyun], Guo, Q.H.[Qing-Hua],
Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data,
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Shen, W.J.[Wen-Juan], Li, M.S.[Ming-Shi], Huang, C.Q.[Cheng-Quan], Wei, A.[Anshi],
Quantifying Live Aboveground Biomass and Forest Disturbance of Mountainous Natural and Plantation Forests in Northern Guangdong, China, Based on Multi-Temporal Landsat, PALSAR and Field Plot Data,
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Schumacher, P.[Paul], Mislimshoeva, B.[Bunafsha], Brenning, A.[Alexander], Zandler, H.[Harald], Brandt, M.[Martin], Samimi, C.[Cyrus], Koellner, T.[Thomas],
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Lin, C.[Chinsu], 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,
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Yan, E.[Enping], Lin, H.[Hui], Wang, G.X.[Guang-Xing], Sun, H.[Hua],
Multi-Resolution Mapping and Accuracy Assessment of Forest Carbon Density by Combining Image and Plot Data from a Nested and Clustering Sampling Design,
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Yang, Y.[Yan], Saatchi, S.S.[Sassan S.], Xu, L.[Liang], Yu, Y.[Yifan], Lefsky, M.A.[Michael A.], White, L.[Lee], Knyazikhin, Y.[Yuri], Myneni, R.B.[Ranga B.],
Abiotic Controls on Macroscale Variations of Humid Tropical Forest Height,
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Tran, C.[Chinh], Yanagida, J.[John],
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Messinger, M.[Max], Asner, G.P.[Gregory P.], Silman, M.[Miles],
Rapid Assessments of Amazon Forest Structure and Biomass Using Small Unmanned Aerial Systems,
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Huang, C.D.[Chu-Dong], Ye, X.Y.[Xin-Yue], Deng, C.B.[Cheng-Bin], Zhang, Z.L.[Zi-Li], Wan, Z.[Zi],
Mapping Above-Ground Biomass by Integrating Optical and SAR Imagery: A Case Study of Xixi National Wetland Park, China,
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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],
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Toraño Caicoya, A., Kugler, F., Hajnsek, I., Papathanassiou, K.P.,
Large-Scale Biomass Classification in Boreal Forests With TanDEM-X Data,
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IEEE DOI 1610
digital elevation models BibRef

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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],
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Wang, Q.A.[Qi-Ang], Pang, Y.[Yong], Li, Z.[Zengyuan], Sun, G.Q.[Guo-Qing], Chen, E.[Erxue], Ni-Meister, W.[Wenge],
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Kachamba, D.J.[Daud Jones], Ørka, H.O.[Hans Ole], Gobakken, T.[Terje], Eid, T.[Tron], Mwase, W.[Weston],
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Estimating Aboveground Biomass in Tropical Forests: Field Methods and Error Analysis for the Calibration of Remote Sensing Observations,
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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],
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An Integrated GNSS/INS/LiDAR-SLAM Positioning Method for Highly Accurate Forest Stem Mapping,
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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],
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DOI Link 1703
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Gwenzi, D.[David], Helmer, E.H.[Eileen H.], Zhu, X.L.[Xiao-Lin], Lefsky, M.A.[Michael A.], Marcano-Vega, H.[Humfredo],
Predictions of Tropical Forest Biomass and Biomass Growth Based on Stand Height or Canopy Area Are Improved by Landsat-Scale Phenology across Puerto Rico and the U.S. Virgin Islands,
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Balenovic, I.[Ivan], Milas, A.S.[Anita Simic], Marjanovic, H.[Hrvoje],
A Comparison of Stand-Level Volume Estimates from Image-Based Canopy Height Models of Different Spatial Resolutions,
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Zhu, J.[Jia], Huang, Z.H.[Zhi-Hong], Sun, H.[Hua], Wang, G.X.[Guang-Xing],
Mapping Forest Ecosystem Biomass Density for Xiangjiang River Basin by Combining Plot and Remote Sensing Data and Comparing Spatial Extrapolation Methods,
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Pargal, S.[Sourabh], Fararoda, R.[Rakesh], Rajashekar, G.[Gopalakrishnan], Balachandran, N.[Natesan], Réjou-Méchain, M.[Maxime], Barbier, N.[Nicolas], Jha, C.S.[Chandra Shekhar], Pélissier, R.[Raphaël], Dadhwal, V.K.[Vinay Kumar], Couteron, P.[Pierre],
Inverting Aboveground Biomass-Canopy Texture Relationships in a Landscape of Forest Mosaic in the Western Ghats of India Using Very High Resolution Cartosat Imagery,
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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,
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Cheng, T.[Tao], Song, R.Z.[Ren-Zhong], Li, D.[Dong], Zhou, K.[Kai], Zheng, H.B.[Heng-Biao], Yao, X.[Xia], Tian, Y.C.[Yong-Chao], Cao, W.X.[Wei-Xing], Zhu, Y.[Yan],
Spectroscopic Estimation of Biomass in Canopy Components of Paddy Rice Using Dry Matter and Chlorophyll Indices,
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Bernasconi, L.[Luca], Chirici, G.[Gherardo], Marchetti, M.[Marco],
Biomass Estimation of Xerophytic Forests Using Visible Aerial Imagery: Contrasting Single-Tree and Area-Based Approaches,
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Liu, K.[Kaili], Wang, J.[Jindi], Zeng, W.[Weisheng], Song, J.[Jinling],
Comparison and Evaluation of Three Methods for Estimating Forest above Ground Biomass Using TM and GLAS Data,
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Peña, M.A., Liao, R., Brenning, A.,
Using spectrotemporal indices to improve the fruit-tree crop classification accuracy,
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Elsevier DOI 1706
Satellite, image, time, series BibRef

de Rivera, Ó.R.[Óscar Rodríguez], López-Quílez, A.[Antonio],
Development and Comparison of Species Distribution Models for Forest Inventories,
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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,
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Kachamba, D.J.[Daud Jones], Ørka, H.O.[Hans Ole], Næsset, E.[Erik], Eid, T.[Tron], Gobakken, T.[Terje],
Influence of Plot Size on Efficiency of Biomass Estimates in Inventories of Dry Tropical Forests Assisted by Photogrammetric Data from an Unmanned Aircraft System,
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Pacheco-Labrador, J.[Javier], El-Madany, T.S.[Tarek S.], Martín, M.P.[M. Pilar], Migliavacca, M.[Mirco], Rossini, M.[Micol], Carrara, A.[Arnaud], Zarco-Tejada, P.J.[Pablo J.],
Spatio-Temporal Relationships between Optical Information and Carbon Fluxes in a Mediterranean Tree-Grass Ecosystem,
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Nunes, M.H.[Matheus H.], Ewers, R.M.[Robert M.], Turner, E.C.[Edgar C.], Coomes, D.A.[David A.],
Mapping Aboveground Carbon in Oil Palm Plantations Using LiDAR: A Comparison of Tree-Centric versus Area-Based Approaches,
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Adhikari, H.[Hari], Heiskanen, J.[Janne], Siljander, M.[Mika], Maeda, E.[Eduardo], Heikinheimo, V.[Vuokko], Pellikka, P.K.E.[Petri K. E.],
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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,
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Yang, T., Zhang, H., Li, Y., Ma, Z.[Zaiyang], Huang, R.[Ruirong], Li, S.[Sijia],
The visual simulation technology in formatting forest management plan at unit level based on WF,
ICIVC17(739-745)
IEEE DOI 1708
Biological system modeling, Density measurement, Force measurement, Knowledge management, Volume measurement, WF, forest management plan formation, visual, simulation 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

Johnson, B.A., Scheyvens, H., Samejima, H., Onoda, M.,
Characteristics Of The Remote Sensing Data Used In The Proposed Unfccc Redd+ Forest Reference Emission Levels (frels),
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Mokroš, M., Tabacák, M., Lieskovský, M., Fabrika, M.,
Unmanned Aerial Vehicle Use For Wood Chips Pile Volume Estimation,
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Yilmaz, V., Serifoglu, C., Gungor, O.,
Determining Stand Parameters From Uas-based Point Clouds,
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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],
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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,
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Kim, K.M.,
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Ibanez, C.A.G., Carcellar, III, B.G., Paringit, E.C., Argamosa, R.J.L., Faelga, R.A.G., Posilero, M.A.V., Zaragosa, G.P., Dimayacyac, N.A.,
Estimating DBH of Trees Employing Multiple Linear Regression Of The Best Lidar-derived Parameter Combination Automated In Python In A Natural Broadleaf Forest In The Philippines,
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Patias, P.[Petros], Stournara, P.[Panagiota],
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De Keersmaecker, W., Lhermitte, S., Tits, L., Honnay, O., Coppin, P., Somers, B.,
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Forest Resources Study In Mongolia Using Advanced Spatial Technologies,
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Sah, B.P., Hämäläinen, J.M., Sah, A.K., Honji, K., Foli, E.G., Awudi, C.,
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Renaudin, E., Mercer, B., Zhang, Q., Collins, M.J.,
Biomass Estimation Using Vertical Forest Structure From Sar Tomograghy: A Case Study In Canadian Boreal Forest.,
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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,
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Forsman, M., Börlin, N., Holmgren, J.,
Estimation Of Tree Stem Attributes Using Terrestrial Photogrammetry,
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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,
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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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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).
PDF File. 0709
BibRef

Andersen, H.E., Breidenbach, J.,
Statistical Properties of Mean Stand Biomass Estimators in a Lidar-Based Double Sampling Forest Survey Design,
Laser07(8).
PDF File. 0709
BibRef

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).
PDF File. 0709
BibRef

Chapter on Cartography, Aerial Images, Remote Sensing, Buildings, Roads, Terrain, ATR continues in
Biomass Measurements for Individual Trees .


Last update:Sep 18, 2017 at 11:34:11