{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,29]],"date-time":"2026-07-29T21:12:02Z","timestamp":1785359522937,"version":"3.55.0"},"reference-count":81,"publisher":"MDPI AG","issue":"7","license":[{"start":{"date-parts":[[2016,7,4]],"date-time":"2016-07-04T00:00:00Z","timestamp":1467590400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>As a large carbon pool, global forest ecosystems are a critical component of the global carbon cycle. Accurate estimations of global forest aboveground biomass (AGB) can improve the understanding of global carbon dynamics and help to quantify anthropogenic carbon emissions. Light detection and ranging (LiDAR) techniques have been proven that can accurately capture both horizontal and vertical forest structures and increase the accuracy of forest AGB estimation. In this study, we mapped the global forest AGB density at a 1-km resolution through the integration of ground inventory data, optical imagery, Geoscience Laser Altimeter System\/Ice, Cloud, and Land Elevation Satellite data, climate surfaces, and topographic data. Over 4000 ground inventory records were collected from published literatures to train the forest AGB estimation model and validate the resulting global forest AGB product. Our wall-to-wall global forest AGB map showed that the global forest AGB density was 210.09 Mg\/ha on average, with a standard deviation of 109.31 Mg\/ha. At the continental level, Africa (333.34 \u00b1 63.80 Mg\/ha) and South America (301.68 \u00b1 67.43 Mg\/ha) had higher AGB density. The AGB density in Asia, North America and Europe were 172.28 \u00b1 94.75, 166.48 \u00b1 84.97, and 132.97 \u00b1 50.70 Mg\/ha, respectively. The wall-to-wall forest AGB map was evaluated at plot level using independent plot measurements. The adjusted coefficient of determination (R2) and root-mean-square error (RMSE) between our predicted results and the validation plots were 0.56 and 87.53 Mg\/ha, respectively. At the ecological zone level, the R2 and RMSE between our map and Intergovernmental Panel on Climate Change suggested values were 0.56 and 101.21 Mg\/ha, respectively. Moreover, a comprehensive comparison was also conducted between our forest AGB map and other published regional AGB products. Overall, our forest AGB map showed good agreements with these regional AGB products, but some of the regional AGB products tended to underestimate forest AGB density.<\/jats:p>","DOI":"10.3390\/rs8070565","type":"journal-article","created":{"date-parts":[[2016,7,4]],"date-time":"2016-07-04T10:04:21Z","timestamp":1467626661000},"page":"565","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":165,"title":["Mapping Global Forest Aboveground Biomass with Spaceborne LiDAR, Optical Imagery, and Forest Inventory Data"],"prefix":"10.3390","volume":"8","author":[{"given":"Tianyu","family":"Hu","sequence":"first","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yanjun","family":"Su","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"Sierra Nevada Research Institute, School of Engineering, University of California at Merced, Merced, CA 95343, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Baolin","family":"Xue","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jin","family":"Liu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiaoqian","family":"Zhao","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jingyun","family":"Fang","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"Department of Ecology, College of Urban and Environmental Sciences, and Key Laboratory for Earth Surface Processes of the Ministry of Education, Peking University, Beijing 100871, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qinghua","family":"Guo","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China"},{"name":"Sierra Nevada Research Institute, School of Engineering, University of California at Merced, Merced, CA 95343, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2016,7,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"525","DOI":"10.1038\/ngeo905","article-title":"Terrestrial biogeochemical feedbacks in the climate system","volume":"3","author":"Arneth","year":"2010","journal-title":"Nat. Geosci."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1444","DOI":"10.1126\/science.1155121","article-title":"Forests and climate change: Forcings, feedbacks, and the climate benefits of forests","volume":"320","author":"Bonan","year":"2008","journal-title":"Science"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1046\/j.1466-822X.2003.00010.x","article-title":"Above-ground biomass estimation in closed canopy neotropical forests using lidar remote sensing: Factors affecting the generality of relationships","volume":"12","author":"Drake","year":"2003","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1029\/96GB02692","article-title":"An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics","volume":"10","author":"Foley","year":"1996","journal-title":"Glob. Biogeochem. Cycle"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"249","DOI":"10.1016\/S0304-3800(96)00034-8","article-title":"A process-based, terrestrial biosphere model of ecosystem dynamics (hybrid v3. 0)","volume":"95","author":"Friend","year":"1997","journal-title":"Ecol. Model."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1046\/j.1365-2486.1998.t01-1-00203.x","article-title":"Terrestrial models and global change: Challenges for the future","volume":"4","author":"Hurtt","year":"1998","journal-title":"Glob. Chang. Biol."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"769","DOI":"10.2307\/1313568","article-title":"Terrestrial biomass and the effects of deforestation on the global carbon cycle results from a model of primary production using satellite observations","volume":"49","author":"Potter","year":"1999","journal-title":"BioScience"},{"key":"ref_8","unstructured":"Houghton, R.A. (1992). Tropical Forests and Climate, Springer."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"731","DOI":"10.1111\/j.1365-2486.2001.00426.x","article-title":"The spatial distribution of forest biomass in the brazilian amazon: A comparison of estimates","volume":"7","author":"Houghton","year":"2001","journal-title":"Glob. Chang. Biol."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"1029","DOI":"10.1126\/science.1117682","article-title":"Species loss and aboveground carbon storage in a tropical forest","volume":"310","author":"Bunker","year":"2005","journal-title":"Science"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"647","DOI":"10.1111\/j.1469-8137.2010.03350.x","article-title":"Multiple mechanisms of amazonian forest biomass losses in three dynamic global vegetation models under climate change","volume":"187","author":"Galbraith","year":"2010","journal-title":"New Phytol."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"11635","DOI":"10.1073\/pnas.0901970106","article-title":"Re-evaluation of forest biomass carbon stocks and lessons from the world\u2019s most carbon-dense forests","volume":"106","author":"Keith","year":"2009","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"988","DOI":"10.1126\/science.1201609","article-title":"A large and persistent carbon sink in the world\u2019s forests","volume":"333","author":"Pan","year":"2011","journal-title":"Science"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"2320","DOI":"10.1126\/science.1058629","article-title":"Changes in forest biomass carbon storage in china between 1949 and 1998","volume":"292","author":"Fang","year":"2001","journal-title":"Science"},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"439","DOI":"10.1111\/j.1654-1103.2002.tb02068.x","article-title":"An international network to monitor the structure, composition and dynamics of amazonian forests (rainfor)","volume":"13","author":"Malhi","year":"2002","journal-title":"J. Veg. Sci."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"945","DOI":"10.1111\/j.1365-2486.2005.00955.x","article-title":"Aboveground forest biomass and the global carbon balance","volume":"11","author":"Houghton","year":"2005","journal-title":"Glob. Chang. Biol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"836","DOI":"10.2307\/1312969","article-title":"Two decades of carbon flux from forests of the pacific northwest","volume":"46","author":"Cohen","year":"1996","journal-title":"BioScience"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/S0034-4257(99)00061-9","article-title":"A global terrestrial monitoring network integrating tower fluxes, flask sampling, ecosystem modeling and eos satellite data","volume":"70","author":"Running","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"240","DOI":"10.1016\/0034-4257(94)90074-4","article-title":"Mapping forest vegetation using landsat tm imagery and a canopy reflectance model","volume":"50","author":"Woodcock","year":"1994","journal-title":"Remote Sens. Environ."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1016\/S0168-1923(99)00112-4","article-title":"Regional forest biomass and wood volume estimation using satellite data and ancillary data","volume":"98","author":"Fazakas","year":"1999","journal-title":"Agric. For. Meteorol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"379","DOI":"10.1046\/j.1466-822X.2001.00248.x","article-title":"Mapping the biomass of bornean tropical rain forest from remotely sensed data","volume":"10","author":"Foody","year":"2001","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/0034-4257(89)90112-0","article-title":"Tropical forest biomass and successional age class relationships to a vegetation index derived from landsat tm data","volume":"28","author":"Sader","year":"1989","journal-title":"Remote Sens. Environ."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"045011","DOI":"10.1088\/1748-9326\/3\/4\/045011","article-title":"A first map of tropical africa\u2019s above-ground biomass derived from satellite imagery","volume":"3","author":"Baccini","year":"2008","journal-title":"Environ. Res. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0034-4257(96)00121-6","article-title":"A study of the relationship between radar backscatter and regenerating tropical forest biomass for spaceborne sar instruments","volume":"60","author":"Luckman","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/36.134089","article-title":"Relating forest biomass to sar data","volume":"30","author":"Toan","year":"1992","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"125","DOI":"10.1016\/S0034-4257(02)00198-0","article-title":"Large-scale mapping of boreal forest in siberia using ers tandem coherence and jers backscatter data","volume":"8","author":"Wagner","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"279","DOI":"10.1016\/S0034-4257(01)00279-6","article-title":"Radiometric slope correction for forest biomass estimation from sar data in the western sayani mountains, siberia","volume":"79","author":"Sun","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"388","DOI":"10.1109\/36.295053","article-title":"Mapping biomass of a northern forest using multifrequency sar data","volume":"32","author":"Ranson","year":"1994","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1726","DOI":"10.1109\/TGRS.2006.887002","article-title":"Estimation of forest fuel load from radar remote sensing","volume":"45","author":"Saatchi","year":"2007","journal-title":"IEEE Trans. Geosci. Remote"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"466","DOI":"10.1016\/j.rse.2012.05.029","article-title":"Mapping forest aboveground biomass in the northeastern united states with alos palsar dual-polarization l-band","volume":"124","author":"Cartus","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1016\/S0034-4257(96)00148-4","article-title":"The use of imaging radars for ecological applications: A review","volume":"59","author":"Kasischke","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1297","DOI":"10.1080\/01431160500486732","article-title":"The potential and challenge of remote sensing-based biomass estimation","volume":"27","author":"Lu","year":"2006","journal-title":"Int. J. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"L23401","DOI":"10.1029\/2009GL040692","article-title":"Using satellite radar backscatter to predict above-ground woody biomass: A consistent relationship across four different african landscapes","volume":"36","author":"Mitchard","year":"2009","journal-title":"Geophys. Res. Lett."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"14784","DOI":"10.1073\/pnas.261555198","article-title":"A large carbon sink in the woody biomass of northern forests","volume":"98","author":"Myneni","year":"2001","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"556","DOI":"10.1038\/nclimate1601","article-title":"Radar backscatter is not a \u2018direct measure\u2019 of forest biomass","volume":"2","author":"Woodhouse","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"216","DOI":"10.1016\/j.isprsjprs.2013.11.009","article-title":"A practical method for srtm dem correction over vegetated mountain areas","volume":"87","author":"Su","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.rse.2004.02.008","article-title":"Small-footprint lidar estimation of sub-canopy elevation and tree height in a tropical rain forest landscape","volume":"91","author":"Clark","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"3876","DOI":"10.1016\/j.rse.2008.06.003","article-title":"Regional aboveground forest biomass using airborne and spaceborne lidar in qu\u00e9bec","volume":"112","author":"Boudreau","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"2931","DOI":"10.1016\/j.rse.2010.08.029","article-title":"Estimation of tropical rain forest aboveground biomass with small-footprint lidar and hyperspectral sensors","volume":"115","author":"Clark","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"L22S02","DOI":"10.1029\/2005GL023971","article-title":"Estimates of forest canopy height and aboveground biomass using icesat","volume":"32","author":"Lefsky","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"2786","DOI":"10.1016\/j.rse.2011.01.026","article-title":"Satellite lidar vs. Small footprint airborne lidar: Comparing the accuracy of aboveground biomass estimates and forest structure metrics at footprint level","volume":"115","author":"Popescu","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"691","DOI":"10.1016\/j.rse.2008.11.010","article-title":"Estimating siberian timber volume using modis and icesat\/glas","volume":"113","author":"Nelson","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2917","DOI":"10.1016\/j.rse.2010.08.027","article-title":"Mapping biomass and stress in the sierra nevada using lidar and hyperspectral data fusion","volume":"115","author":"Swatantran","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2683","DOI":"10.5194\/bg-9-2683-2012","article-title":"High-resolution mapping of forest carbon stocks in the colombian amazon","volume":"9","author":"Asner","year":"2012","journal-title":"Biogeosciences"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"198","DOI":"10.1016\/j.isprsjprs.2015.02.007","article-title":"Lidar with multi-temporal modis provide a means to upscale predictions of forest biomass","volume":"102","author":"Li","year":"2015","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","unstructured":"Simard, M., Pinto, N., Fisher, J.B., and Baccini, A. (2011). Mapping forest canopy height globally with spaceborne lidar. J. Geophys. Res. Biogeosci., 116.","DOI":"10.1029\/2011JG001708"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/j.rse.2015.12.002","article-title":"Spatial distribution of forest aboveground biomass in china: Estimation through combination of spaceborne lidar, optical imagery, and forest inventory data","volume":"173","author":"Su","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"9899","DOI":"10.1073\/pnas.1019576108","article-title":"Benchmark map of forest carbon stocks in tropical regions across three continents","volume":"108","author":"Saatchi","year":"2011","journal-title":"Proc. Natl. Acad. Sci. USA"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1038\/nclimate1354","article-title":"Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps","volume":"2","author":"Baccini","year":"2012","journal-title":"Nat. Clim. Chang."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1109\/JSTARS.2013.2256883","article-title":"Forest biomass mapping of northeastern China using glas and modis data","volume":"7","author":"Zhang","year":"2014","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.rse.2014.01.025","article-title":"Estimation of forest aboveground biomass in california using canopy height and leaf area index estimated from satellite data","volume":"151","author":"Zhang","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"5534","DOI":"10.3390\/rs70505534","article-title":"National forest aboveground biomass mapping from icesat\/glas data and modis imagery in China","volume":"7","author":"Chi","year":"2015","journal-title":"Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.rse.2013.06.019","article-title":"Taking stock of circumboreal forest carbon with ground measurements, airborne and spaceborne lidar","volume":"137","author":"Neigh","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"297","DOI":"10.1111\/geb.12125","article-title":"Carbon stock and density of northern boreal and temperate forests","volume":"23","author":"Thurner","year":"2014","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_55","unstructured":"Guo, Q. Global Forest Aboveground Biomass. Available online: http:\/\/guolablidar.com\/."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"1965","DOI":"10.1002\/joc.1276","article-title":"Very high resolution interpolated climate surfaces for global land areas","volume":"25","author":"Hijmans","year":"2005","journal-title":"Int. J. Climatol."},{"key":"ref_57","unstructured":"Jarvis, A., Reuter, H.I., Nelson, A., and Guevara, E. Hole-Filled Srtm for the Globe Version 4. Available online:http:\/\/srtm.csi.cgiar.org."},{"key":"ref_58","unstructured":"Carroll, M., DiMiceli, C., Sohlberg, R., and Townshend, J. (2004). 1 km Modis Normalized Difference Vegetation Index, University of Maryland."},{"key":"ref_59","unstructured":"Channan, S., Collins, K., and Emanuel, W. (2014). Global Mosaics of the Standard Modis Land Cover Type Data, University of Maryland and the Pacific Northwest National Laboratory."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1016\/j.rse.2009.08.016","article-title":"MODIS collection 5 global land cover: Algorithm refinements and characterization of new datasets","volume":"114","author":"Friedl","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"L21S01","DOI":"10.1029\/2005GL024009","article-title":"Overview of the icesat mission","volume":"32","author":"Schutz","year":"2005","journal-title":"Geophys. Res. Lett."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"013537","DOI":"10.1117\/1.2795724","article-title":"Revised method for forest canopy height estimation from geoscience laser altimeter system waveforms","volume":"1","author":"Lefsky","year":"2007","journal-title":"J. Appl. Remote Sens."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"L15401","DOI":"10.1029\/2010GL043622","article-title":"A global forest canopy height map from the moderate resolution imaging spectroradiometer and the geoscience laser altimeter system","volume":"37","author":"Lefsky","year":"2010","journal-title":"Geophys. Res. Lett."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"11202","DOI":"10.3390\/rs70911202","article-title":"Srtm dem correction in vegetated mountain areas through the integration of spaceborne lidar, airborne lidar, and optical imagery","volume":"7","author":"Su","year":"2015","journal-title":"Remote Sens."},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Farr, T.G., Rosen, P.A., Caro, E., Crippen, R., Duren, R., Hensley, S., Kobrick, M., Paller, M., Rodriguez, E., and Roth, L. (2007). The shuttle radar topography mission. Rev. Geophys., 45.","DOI":"10.1029\/2005RG000183"},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1016\/S0924-2716(02)00124-7","article-title":"The shuttle radar topography mission\u2014A new class of digital elevation models acquired by spaceborne radar","volume":"57","author":"Rabus","year":"2003","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"397","DOI":"10.1007\/s00442-002-1115-1","article-title":"Changes in biomass, productivity and decomposition along topographical gradients under different geological conditions in tropical lower montane forests on mount kinabalu, borneo","volume":"134","author":"Takyu","year":"2003","journal-title":"Oecologia"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1107","DOI":"10.1111\/j.1365-2486.2006.01120.x","article-title":"The regional variation of aboveground live biomass in old-growth amazonian forests","volume":"12","author":"Malhi","year":"2006","journal-title":"Glob. Chang. Biol."},{"key":"ref_69","first-page":"18","article-title":"Classification and regression by randomforest","volume":"2","author":"Liaw","year":"2002","journal-title":"R News"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"346","DOI":"10.1016\/j.envsoft.2004.11.013","article-title":"The map comparison kit","volume":"21","author":"Visser","year":"2006","journal-title":"Environ. Model. Softw."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1186\/1750-0680-6-7","article-title":"Mapping biomass with Remote Sensing: A comparison of methods for the case study of uganda","volume":"6","author":"Avitabile","year":"2011","journal-title":"Carbon Balance Manag."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"1406","DOI":"10.1111\/gcb.13139","article-title":"An integrated pan-tropical biomass map using multiple reference datasets","volume":"22","author":"Avitabile","year":"2016","journal-title":"Glob. Chang. Biol."},{"key":"ref_73","unstructured":"Ruesch, A., and Gibbs, H.K. (2008). New IPCC Tier-1 Global Biomass Carbon Map for the Year 2000, Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"838","DOI":"10.1139\/cjfr-2015-0006","article-title":"Combining satellite lidar, airborne lidar, and ground plots to estimate the amount and distribution of aboveground biomass in the boreal forest of north america","volume":"45","author":"Margolis","year":"2015","journal-title":"Can. J. For. Res."},{"key":"ref_75","unstructured":"Neigh, C.S., Nelson, R.F., Ranson, K.J., Margolis, H., Montesano, P.M., Sun, G., Kharuk, V., Naesset, E., Wulder, M.A., and Anderson, H. (2015). Lidar-Based Biomass Estimates, Boreal Forest Biome, Eurasia, 2005\u20132006, ORNL Distributed Active Archive Center."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"1658","DOI":"10.1016\/j.rse.2007.08.021","article-title":"Mapping us forest biomass using nationwide forest inventory data and moderate resolution information","volume":"112","author":"Blackard","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_77","unstructured":"Saatchi, S., Yu, Y., Alex, F., Nuemann, M., Chapman, B., Nemani, R., Ganguly, S., and Zhang, G. (2005). CMS US Forest Biomass Map, Available online:http:\/\/carbon.nasa.gov\/cgi-bin\/cms\/inv_pgp.pl?pgid=582&format=1."},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"935","DOI":"10.1111\/geb.12168","article-title":"Markedly divergent estimates of amazon forest carbon density from ground plots and satellites","volume":"23","author":"Mitchard","year":"2014","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"1081","DOI":"10.5194\/bg-8-1081-2011","article-title":"Height-diameter allometry of tropical forest trees","volume":"8","author":"Feldpausch","year":"2011","journal-title":"Biogeosciences"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"490","DOI":"10.1016\/j.rse.2010.09.018","article-title":"Retrieval of growing stock volume in boreal forest using hyper-temporal series of envisat asar scansar backscatter measurements","volume":"115","author":"Santoro","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_81","first-page":"777","article-title":"Temperate forest height estimation performance using ICESat GLAS data from different observation periods","volume":"37","author":"Pang","year":"2008","journal-title":"Int. Arch. Photogram. Remote Sens. Spat. Inf. Sci."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/7\/565\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T19:25:25Z","timestamp":1760210725000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/8\/7\/565"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,7,4]]},"references-count":81,"journal-issue":{"issue":"7","published-online":{"date-parts":[[2016,7]]}},"alternative-id":["rs8070565"],"URL":"https:\/\/doi.org\/10.3390\/rs8070565","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,7,4]]}}}