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IPCC Guidelines for National Greenhouse Gas Inventories Volume\u2014IV Agriculture, Forestry and other Land-Use, Institute of Global Environmental Strategies (IGES)."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s004420050201","article-title":"Root biomass allocation in the world\u2019s upland forests","volume":"111","author":"Cairns","year":"1997","journal-title":"Oecologia"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"165","DOI":"10.1038\/nature04514","article-title":"Temperature sensitivity of soil carbon decomposition and feedbacks to climate change","volume":"440","author":"Davidson","year":"2006","journal-title":"Nature"},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Houghton, R.A., Hall, F., and Goetz, S.J. (2009). Importance of biomass in the global carbon cycle. J. Geophys. Res., 114.","DOI":"10.1029\/2009JG000935"},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1088\/1748-9326\/2\/4\/045023","article-title":"Monitoring and estimating tropical forest carbon stocks: Making REDD a reality","volume":"2","author":"Gibbs","year":"2007","journal-title":"Environ. Res. Lett."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"581","DOI":"10.1016\/j.isprsjprs.2010.09.001","article-title":"Status and future of laser scanning, synthetic aperture radar and hyperspectral remote sensing data for forest biomass assessment","volume":"65","author":"Koch","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_7","unstructured":"Angelsen, A., and Hofstad, O. (2017, September 08). Inputs to the Development of a National REDD Strategy in Tanzania.. Available online: http:\/\/cf.tfcg.org\/pubs\/Angelsen2008REDD%20Tanzania%20rpt.pdf."},{"key":"ref_8","unstructured":"United Nations (December, January 28). Outcome of the Ad Hoc Working Group on longterm cooperative action under the convention. Proceedings of the United Nations Framework Convention on Climate Change (2011), Durban, South Africa."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"149","DOI":"10.1016\/S0378-1127(98)00475-7","article-title":"Allometric regressions for improved estimate of secondary forest biomass in the Central Amazon","volume":"117","author":"Nelson","year":"1999","journal-title":"For. Ecol. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1016\/j.foreco.2004.07.062","article-title":"Allometric relationships for below- and aboveground biomass of young Scots pines","volume":"203","author":"Wang","year":"2004","journal-title":"For. Ecol. Manag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"37","DOI":"10.1016\/S0378-1127(99)00188-7","article-title":"A non-destructive method for estimating above-ground forest biomass in threatened woodlands","volume":"130","author":"Gauquelin","year":"2000","journal-title":"For. Ecol. Manag."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.foreco.2008.09.028","article-title":"Allometric equations for tree species and carbon stocks for forests of Northwestern Mexico","volume":"257","year":"2009","journal-title":"For. Ecol. Manag."},{"key":"ref_13","first-page":"881","article-title":"Biomass estimation methods for tropical forests with applications to forest inventory data","volume":"35","author":"Brown","year":"1989","journal-title":"For. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1684","DOI":"10.1016\/j.foreco.2009.01.027","article-title":"Allometric equations for estimating the above-ground biomass in tropical lowland dipterocarp forests","volume":"257","author":"Basuki","year":"2009","journal-title":"For. Ecol. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","unstructured":"Kumar, L., Sinha, P., Taylor, S., and Alqurashi, A.F. (2015). Review of the use of remote sensing for biomass estimation to support renewable energy generation. J. Appl. Remote Sens., 9.","DOI":"10.1117\/1.JRS.9.097696"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"5447","DOI":"10.1080\/01431160412331291279","article-title":"Biomass estimations and carbon stock calculations in the oil palm plantations of African derived savannas using IKONOS data","volume":"25","author":"Thenkabail","year":"2004","journal-title":"Int. J. Remote Sens."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"63","DOI":"10.1016\/j.rse.2006.01.021","article-title":"Mapping forest structure for wildlife habitat analysis using multi-sensor (LiDAR, SAR\/InSAR, ETM+, Quickbird) synergy","volume":"102","author":"Hyde","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1016\/S0034-4257(03)00039-7","article-title":"Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions","volume":"85","author":"Foody","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1139","DOI":"10.1080\/014311600210119","article-title":"Satellite estimation of tropical secondary forest above-ground biomass: Data from Brazil and Bolivia","volume":"21","author":"Steininger","year":"2000","journal-title":"Int. J. Remote Sens."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"402","DOI":"10.1016\/j.rse.2004.08.008","article-title":"Estimating aboveground biomass using Landsat 7 ETM data across a managed landscape in northern Wisconsin, USA","volume":"93","author":"Zheng","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Baccini, A., Friedl, M.A., Woodcock, C.E., and Warbington, R. (2004). Forest biomass estimation over regional scales using multisource data. Geophys. Res. Lett., 31.","DOI":"10.1029\/2004GL019782"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1016\/S0034-4257(02)00130-X","article-title":"Remote sensing estimates of boreal and temperate forest woody biomass: Carbon pools, sources, and sinks","volume":"84","author":"Dong","year":"2003","journal-title":"Remote Sens. 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Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"10","DOI":"10.1007\/s11461-008-0013-z","article-title":"Modeling forest aboveground biomass by combining spectrum, textures and topographic features","volume":"3","author":"Li","year":"2008","journal-title":"Front. For. China"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"434","DOI":"10.1016\/j.rse.2005.09.011","article-title":"Estimating biomass for boreal forests using ASTER satellite data combined with standwise forest inventory data","volume":"99","author":"Muukkonen","year":"2005","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. Electron."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"1458","DOI":"10.1109\/36.843042","article-title":"BioSAR (TM): An inexpensive airborne VHF multiband SAR system for vegetation biomass measurement","volume":"38","author":"Imhoff","year":"2000","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/S0034-4257(01)00236-X","article-title":"Retrieval biomass of a large Venezuelan pine plantation using JERS-1 SAR data. Analysis of forest structure impact on radar signature","volume":"79","author":"Castel","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_31","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_32","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1016\/j.rse.2002.12.001","article-title":"Airborne P-band SAR applied to the aboveground biomass studies in the Brazilian tropical rainforest","volume":"87","author":"Santos","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_33","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\u2014A review","volume":"59","author":"Kasischke","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_34","unstructured":"Ustin, S.L. (2004). Temperate and boreal forests. Remote Sensing for Natural Resource Management and Environmental Monitoring, John Wiley & Sons."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3371","DOI":"10.1109\/TGRS.2012.2219872","article-title":"Forest biomass estimation using texture measurements of high resolution dual-polarization C-band SAR data","volume":"51","author":"Sarker","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","unstructured":"Buckley, J.R., and Smith, A.M. (2010). Monitoring grasslands with RADARSAT 2 quad-pol imagery. IEEE Int. Geosci. Remote Sens. Symp., 3090\u20133093.","DOI":"10.1109\/IGARSS.2010.5652367"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"403","DOI":"10.1109\/36.134089","article-title":"Relating forest biomass to SAR data","volume":"30","author":"Beaudoin","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"1217","DOI":"10.1080\/01431160110092867","article-title":"Savanna and tropical rainforest biomass estimation and spatialization using JERS-1 data","volume":"23","author":"Santos","year":"2002","journal-title":"Int. J. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"159","DOI":"10.1177\/030913330102500201","article-title":"Forest mapping and monitoring with interferometric synthetic aperture radar (InSAR)","volume":"25","author":"Balzter","year":"2001","journal-title":"Progr. Phys. Geogr."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"2777","DOI":"10.1080\/01431169408954284","article-title":"Retrieval of forest biomass from SAR data","volume":"15","author":"Beaudoin","year":"1994","journal-title":"Int. J. Remote Sens."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"223","DOI":"10.1016\/S0034-4257(96)00155-1","article-title":"Evaluation of approaches to estimating aboveground biomass in Southern pine forests using SIR-C data","volume":"59","author":"Harrell","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"2850","DOI":"10.1016\/j.rse.2011.03.020","article-title":"The BIOMASS mission: Mapping global forest biomass to better understand the terrestrial carbon cycle","volume":"115","author":"Quegan","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1002\/aqc.833","article-title":"The potential of L-band SAR for quantifying mangrove characteristics and change: Case studies from the tropics","volume":"17","author":"Lucas","year":"2007","journal-title":"Aquat. Conserv. Mar. Freshwater Ecosyst."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"2353","DOI":"10.1016\/j.rse.2010.05.011","article-title":"Estimating spruce and pine biomass with interferometric X-band SAR","volume":"114","author":"Solberg","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"368","DOI":"10.1016\/j.rse.2004.07.016","article-title":"Quantifying forest above ground carbon content using LiDAR remote sensing","volume":"93","author":"Patenaude","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"189","DOI":"10.1016\/j.foreco.2004.12.001","article-title":"Estimating stand structure using discrete-return LiDAR: An example from low density, fire prone ponderosa pine forests","volume":"208","author":"Hall","year":"2005","journal-title":"For. Ecol. Manag."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"7592","DOI":"10.3390\/rs6087592","article-title":"Sub-compartment variation in tree height, stem diameter and stocking in a Pinus. radiata D. Don plantation examined using airborne LiDAR data","volume":"6","author":"Saremi","year":"2014","journal-title":"Remote Sens."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1007\/s00468-014-0985-2","article-title":"Airborne LiDAR derived canopy height model reveals a significant difference in radiata pine (Pinus. radiata D. Don) heights based on slope and aspect of sites","volume":"28","author":"Saremi","year":"2014","journal-title":"Trees"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"923","DOI":"10.14358\/PERS.72.8.923","article-title":"Isolating individual trees in a savanna woodland using small footprint LiDAR data","volume":"72","author":"Chen","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1080\/02827580410019490","article-title":"Estimation of above ground forest biomass from airborne discrete return laser scanner data using canopy-based quantile estimators","volume":"19","author":"Lim","year":"2004","journal-title":"Scand. J. For. Res."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1016\/j.biombioe.2007.06.022","article-title":"Estimating biomass of individual pine trees using airborne LiDAR","volume":"31","author":"Popescu","year":"2007","journal-title":"Biomass Bioenergy"},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/S0034-4257(01)00243-7","article-title":"Estimating tree height and tree crown properties using airborne scanning laser in a boreal nature reserve","volume":"79","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(92)90056-P","article-title":"Estimating structural attributes of Douglas-fir\/western hemlock forest stands from Landsat and SPOT imagery","volume":"41","author":"Cohen","year":"1992","journal-title":"Remote Sens. Environ."},{"key":"ref_54","unstructured":"Loos, R., Niemann, O., and Visintini, F. (November, January 28). Identification of partial canopies using first and last return LiDAR data. Proceedings of the Our Common Borders\u2014Safety, Security, and the Environment through Remote Sensing, Ottawa, ON, Canada."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1016\/j.rse.2009.11.021","article-title":"Estimating biomass carbon stocks for a Mediterranean forest in central Spain using LiDAR height and intensity data","volume":"114","author":"Riano","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Schucknecht, A., Meroni, M., Kayitakire, F., and Boureima, A. (2017). Phenology-based biomass estimation to support rangeland management in semi-arid environments. Remote Sens., 9.","DOI":"10.3390\/rs9050463"},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Lumbierres, M., M\u00e9ndez, P., Bustamante, J., Soriguer, R., and Santamar\u00eda, L. (2017). Modeling biomass production in seasonal wetlands using MODIS NDVI land surface phenology. Remote Sens., 9.","DOI":"10.3390\/rs9040392"},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Liu, N., Harper, R., Handcock, R., Evans, B., Sochacki, S., Dell, B., Walden, L., and Liu, S. (2017). Seasonal timing for estimating carbon mitigation in revegetation of abandoned agricultural land with high spatial resolution remote sensing. Remote Sens., 9.","DOI":"10.3390\/rs9060545"},{"key":"ref_59","doi-asserted-by":"crossref","unstructured":"Feng, Y., Wu, J., Zhang, J., Zhang, X., and Song, C. (2017). Identifying the relative contributions of climate and grazing to both direction and magnitude of alpine grassland productivity dynamics from 1993 to 2011 on the Northern Tibetan Plateau. Remote Sens., 9.","DOI":"10.3390\/rs9020136"},{"key":"ref_60","doi-asserted-by":"crossref","unstructured":"Awaya, Y., and Takahashi, T. (2017). Evaluating the differences in modeling biophysical attributes between deciduous broadleaved and evergreen conifer forests using low-density small-footprint LiDAR data. Remote Sens., 9.","DOI":"10.3390\/rs9060572"},{"key":"ref_61","doi-asserted-by":"crossref","unstructured":"Vaglio Laurin, G., Pirotti, F., Callegari, M., Chen, Q., Cuozzo, G., Lingua, E., Notarnicola, C., and Papale, D. (2017). Potential of ALOS2 and NDVI to estimate forest above-ground biomass, and comparison with Lidar-derived estimates. Remote Sens., 9.","DOI":"10.3390\/rs9010018"},{"key":"ref_62","doi-asserted-by":"crossref","unstructured":"Schmidt, M., Carter, J., Stone, G., and O\u2019Reagain, P. (2016). Integration of optical and X-band radar data for pasture biomass estimation in an open savannah woodland. Remote Sens., 8.","DOI":"10.3390\/rs8120989"},{"key":"ref_63","doi-asserted-by":"crossref","unstructured":"Meng, B., Ge, J., Liang, T., Yang, S., Gao, J., Feng, Q., Cui, X., Huang, X., and Xie, H. (2017). Evaluation of remote sensing inversion error for the above-ground biomass of alpine meadow grassland based on multi-source satellite data. Remote Sens., 9.","DOI":"10.3390\/rs9040372"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Liu, K., Wang, J., Zeng, W., and Song, J. (2017). Comparison and evaluation of three methods for estimating forest above ground biomass using TM and GLAS data. Remote Sens., 9.","DOI":"10.3390\/rs9040341"},{"key":"ref_65","doi-asserted-by":"crossref","unstructured":"Sibanda, M., Mutanga, O., Rouget, M., and Kumar, L. (2017). estimating biomass of native grass grown under complex management treatments using WorldView-3 spectral derivatives. Remote Sens., 9.","DOI":"10.3390\/rs9010055"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Jin, X., Kumar, L., Li, Z., Xu, X., Yang, G., and Wang, J. (2016). Estimation of winter wheat biomass and yield by combining the AquaCrop model and field hyperspectral data. Remote Sens., 8.","DOI":"10.3390\/rs8120972"},{"key":"ref_67","doi-asserted-by":"crossref","unstructured":"Moeckel, T., Safari, H., Reddersen, B., Fricke, T., and Wachendorf, M. (2017). Fusion of ultrasonic and spectral sensor data for improving the estimation of biomass in grasslands with heterogeneous sward structure. Remote Sens., 9.","DOI":"10.3390\/rs9010098"},{"key":"ref_68","doi-asserted-by":"crossref","unstructured":"Cheng, T., Song, R., Li, D., Zhou, K., Zheng, H., Yao, X., Tian, Y., Cao, W., and Zhu, Y. (2017). Spectroscopic estimation of biomass in canopy components of paddy rice using dry matter and chlorophyll indices. Remote Sens., 9.","DOI":"10.3390\/rs9040319"},{"key":"ref_69","doi-asserted-by":"crossref","unstructured":"Wang, Q., Pang, Y., Li, Z., Sun, G., Chen, E., and Ni-Meister, W. (2016). The potential of forest biomass inversion based on vegetation indices using multi-angle CHRIS\/PROBA data. Remote Sens., 8.","DOI":"10.3390\/rs8110891"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"3999","DOI":"10.1080\/01431160310001654923","article-title":"Narrow band vegetation indices overcome the saturation problem in biomass estimation","volume":"25","author":"Mutanga","year":"2004","journal-title":"Int. J. 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