{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T14:25:37Z","timestamp":1770906337416,"version":"3.50.1"},"reference-count":80,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2013,12,27]],"date-time":"2013-12-27T00:00:00Z","timestamp":1388102400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/3.0\/"}],"content-domain":{"domain":["www.mdpi.com"],"crossmark-restriction":true},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>This study evaluated the accuracy of boreal forest above-ground biomass (AGB) and volume estimates obtained using airborne laser scanning (ALS) and RapidEye data in a two-phase sampling method. Linear regression-based estimation was employed using an independent validation dataset and the performance was evaluated by assessing the bias and the root mean square error (RMSE). In the phase I, ALS data from 50 field plots were used to predict AGB and volume for the 200 surrogate plots. In the phase II, the  ALS-simulated surrogate plots were used as a ground-truth to estimate AGB and volume from the RapidEye data for the study area. The resulting RapidEye models were validated against a separate set of 28 plots. The RapidEye models showed a promising accuracy with a relative RMSE of 19%\u201320% for both volume and AGB. The evaluated concept of biomass inventory would be useful to support future forest monitoring and decision making for sustainable use of forest resources.<\/jats:p>","DOI":"10.3390\/rs6010285","type":"journal-article","created":{"date-parts":[[2013,12,27]],"date-time":"2013-12-27T12:54:46Z","timestamp":1388148886000},"page":"285-309","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["Training Area Concept in a Two-Phase Biomass Inventory Using Airborne Laser Scanning and RapidEye Satellite Data"],"prefix":"10.3390","volume":"6","author":[{"given":"Parvez","family":"Rana","sequence":"first","affiliation":[{"name":"School of Forest Sciences, University of Eastern Finland, P.O. Box-111, FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timo","family":"Tokola","sequence":"additional","affiliation":[{"name":"School of Forest Sciences, University of Eastern Finland, P.O. Box-111, FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lauri","family":"Korhonen","sequence":"additional","affiliation":[{"name":"School of Forest Sciences, University of Eastern Finland, P.O. Box-111, FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Qing","family":"Xu","sequence":"additional","affiliation":[{"name":"School of Forest Sciences, University of Eastern Finland, P.O. Box-111, FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Timo","family":"Kumpula","sequence":"additional","affiliation":[{"name":"Department of Geographical and Historical Studies, University of Eastern Finland,  Yliopistonkatu 7, FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Petteri","family":"Vihervaara","sequence":"additional","affiliation":[{"name":"Finnish Environment Institute (SYKE), Natural Environment Centre, Ecosystem Change Unit,  P.O. Box 111, Yliopistokatu 7 (Natura), FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Laura","family":"Mononen","sequence":"additional","affiliation":[{"name":"Finnish Environment Institute (SYKE), Natural Environment Centre, Ecosystem Change Unit,  P.O. Box 111, Yliopistokatu 7 (Natura), FI-80101 Joensuu, Finland"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2013,12,27]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1007\/BF01105000","article-title":"Forest management and carbon storage: An analysis of 12 key forest nations","volume":"70","author":"Winjum","year":"1993","journal-title":"Water Air Soil Pollut"},{"key":"ref_2","unstructured":"United Nations Framework Convention on Climate Change (UNFCCC) Kyoto Protocol Reference Manual on Accounting of Emissions and Assigned Amounts. Available online: http:\/\/unfccc.int\/files\/national_reports\/accounting_reporting_and_review_under_the_kyoto_protocol\/application\/pdf\/rm_final.pdf."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"441","DOI":"10.1016\/S1462-9011(03)00070-4","article-title":"A review of remote sensing technology in support of the Kyoto protocol","volume":"6","author":"Rosenqvist","year":"2003","journal-title":"Environ. Sci. Policy"},{"key":"ref_4","unstructured":"Intergovernmental Panel on Climate Change (IPCC) (2003). Good Practice Guidance for Land Use, Land-Use Change and Forestry, IPCC National Greenhouse Gas Inventories Programme."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"861","DOI":"10.1111\/j.1468-2346.2006.00575.x","article-title":"The role of forests in global climate change: Whence we come and where we go","volume":"82","author":"Streck","year":"2006","journal-title":"Int. Aff"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1695","DOI":"10.1111\/j.1749-8198.2010.00401.x","article-title":"Digital remote sensing within the field of land change science: Past, present and future directions","volume":"4","author":"Southworth","year":"2010","journal-title":"Geogr. Compass"},{"key":"ref_7","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_8","doi-asserted-by":"crossref","first-page":"816","DOI":"10.1111\/j.1365-2486.2007.01323.x","article-title":"Distribution of aboveground live biomass in the Amazon basin","volume":"13","author":"Saatchi","year":"2007","journal-title":"Glob. Chang. Biol"},{"key":"ref_9","unstructured":"Global Observation of Forest and Land Cover Dynamics (GOFC-GOLD) (2009). Reducing Greenhouse Gas Emissions from Deforestation and Degradation in Developing Countries: A Sourcebook of Methods and Procedures for Monitoring, Measuring and Reporting, GOFC-GOLD Project Office, Natural Resources Canada. GOFC-GOLD Report Version COP14-2;."},{"key":"ref_10","unstructured":"Wilkie, M.L. (2010). Global Forest Resource Assessment Report, Finland, FAO Forestry Department VialedelleTerme di Caracalla. FRA Report No. 69;."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"698","DOI":"10.1038\/386698a0","article-title":"Increased plant growth in the northern high latitudes from 1981 to 1991","volume":"386","author":"Myneni","year":"1997","journal-title":"Nature"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"3211","DOI":"10.1080\/014311697217053","article-title":"A new methodology for the estimation of biomass of conifer dominated boreal forest using NOAA AVHRR data","volume":"18","author":"Hame","year":"1997","journal-title":"Int. J. Remote Sens"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"70","DOI":"10.1126\/science.256.5053.70","article-title":"Biomass and carbon budget of European forests, 1971 to 1990","volume":"256","author":"Kauppi","year":"1992","journal-title":"Science"},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"482","DOI":"10.1080\/02827580410019553","article-title":"US Laser scanning of forest resources: The Nordic experience","volume":"19","author":"Gobakken","year":"2004","journal-title":"Scand. J. For. Res"},{"key":"ref_15","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 ALS remote sensing: Factors affecting the generality of relationships","volume":"12","author":"Drake","year":"2003","journal-title":"Glob. Ecol. Biogeogr"},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1007\/s10021-008-9221-5","article-title":"Environmental and biotic controls over aboveground biomass throughout a rain forest","volume":"12","author":"Asner","year":"2009","journal-title":"Ecosystems"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"776","DOI":"10.1016\/j.isprsjprs.2011.09.005","article-title":"Use of ALS, Airborne CIR and ALOS AVNIR-2 data for estimating tropical forest attributes in Lao PDR","volume":"66","author":"Hou","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"23","DOI":"10.1093\/forestry\/cpq039","article-title":"Different plot selection strategies for field training data in ALS-assisted forest inventory","volume":"84","author":"Maltamo","year":"2011","journal-title":"Forestry"},{"key":"ref_19","first-page":"23","article-title":"Applying satellite imagery for forest planning","volume":"56","author":"Watt","year":"2011","journal-title":"NZ J. For"},{"key":"ref_20","unstructured":"Ozdemir, I., Ozkan, K., Mert, A., Ozkan, U.Y., Senturk, O., and Alkan, O. Mapping Forest Stand Structural Diversity Using Rapideye Satellite Data. Available online: http:\/\/congrexprojects.com\/docs\/12c04_docs2\/poster2_6_ozdemir.pdf."},{"key":"ref_21","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":"Garcia","year":"2010","journal-title":"Remote Sens. Environ"},{"key":"ref_22","unstructured":"Gautam, B.R. (2011). LiDAR-Assisted Multi-source Program (LAMP) for FRA Nepal, MoFSC\/Department of Forest Research and Survey. FRA Bulletin No. 1;."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"460","DOI":"10.1109\/TSMC.1978.4309999","article-title":"Textural features corresponding to visual perception","volume":"8","author":"Tamura","year":"1978","journal-title":"IEEE Trans. Syst. Man Cybern"},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"610","DOI":"10.1109\/TSMC.1973.4309314","article-title":"Textural features for image classification","volume":"3","author":"Haralick","year":"1973","journal-title":"IEEE Trans. Syst. Man Cybern"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"256","DOI":"10.1016\/j.rse.2004.10.001","article-title":"Performance of different spectral and textural aerial photograph features in multi-source forest inventory","volume":"94","author":"Tuominen","year":"2005","journal-title":"Remote Sens. Environ"},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/j.rse.2007.01.005","article-title":"The k-MSN method for the prediction of species specific stand attributes using airborne laser scanning and aerial photographs","volume":"109","author":"Maltamo","year":"2007","journal-title":"Remote Sens. Environ"},{"key":"ref_27","first-page":"67","article-title":"Forest inventory by means of tree-wise 3D-measurements of laser scanning data and digital aerial photographs","volume":"XXXVI-8\/W2","author":"Holopainen","year":"2012","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci"},{"key":"ref_28","unstructured":"Tegel, K. (2011). A Comparison of Landsat-7 ETM+ and Terrasar-X Satellite Imagery in Estimating Forest Aboveground Biomass in a Two-Stage Sampling Procedure, M.Sc. Dissertation,."},{"key":"ref_29","unstructured":"Gautam, B., Peuhkurinen, J., Kauranne, T., Gunia, K., Tegel, K., Latva-K\u00e4yr\u00e4, P., Rana, P., Eivazi, A., Kolesnikov, A., and H\u00e4m\u00e4l\u00e4inen, J. (2013, January 12\u201313). Estimation of Forest Carbon Using LiDAR-Assisted Multi-Source Programme (LAMP) in Nepal. Pokhara, Nepal."},{"key":"ref_30","first-page":"1","article-title":"Taper curve and volume function for pine, spruce and birch","volume":"108","author":"Laasasenaho","year":"1982","journal-title":"Commun. Instituti. For. Fenn"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"625","DOI":"10.14214\/sf.184","article-title":"Biomass equations for scots pine and norway spruce in Finland","volume":"43","author":"Repola","year":"2009","journal-title":"Silva. Fenn"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"605","DOI":"10.14214\/sf.236","article-title":"Biomass equations for birch in Finland","volume":"42","author":"Repola","year":"2008","journal-title":"Silva. Fenn"},{"key":"ref_33","unstructured":"RapidEye RapidEye\u2014Delivering the World. Available online: http:\/\/www.rapideye.de."},{"key":"ref_34","unstructured":"Axelsson, P. (2000, January 16\u201322). DEM Generation from Laser Scanner Data Using Adaptive TIN Models. Amsterdam, The Netherlands."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"164","DOI":"10.1080\/02827580310019257","article-title":"Practical large-scale forest stand inventory using small-footprint airborne scanning laser","volume":"19","year":"2004","journal-title":"Scand. J. For. Res"},{"key":"ref_36","first-page":"257","article-title":"Estimation of forest stand parameters from airborne laser scanning using calibrated plot databases","volume":"56","author":"Junttila","year":"2010","journal-title":"For. Sci"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1016\/S0034-4257(01)00290-5","article-title":"Predicting forest stand characteristics with airborne scanning laser using a practical two-stage procedure and field data","volume":"80","year":"2002","journal-title":"Remote Sens. Environ"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"230","DOI":"10.1016\/S0034-4257(00)00169-3","article-title":"Classification and change detection using Landsat TM data: When and how to correct atmospheric effects?","volume":"75","author":"Song","year":"2001","journal-title":"Remote Sens. Environ"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1016\/S0034-4257(02)00029-9","article-title":"Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection","volume":"82","author":"Du","year":"2002","journal-title":"Remote Sens. Environ"},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"69","DOI":"10.1016\/j.isprsjprs.2011.12.008","article-title":"Relative radiometric correction of multi-temporal ALOS AVNIR-2 data for the estimation of forest attributes","volume":"68","author":"Xu","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"5397","DOI":"10.3390\/s8095397","article-title":"Long-term satellite NDVI data sets: Evaluating their ability to detect ecosystem functional changes in South America","volume":"8","author":"Baldi","year":"2008","journal-title":"Sensors"},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1089\/ast.2005.5.372","article-title":"Vegetation\u2019s red-edge: A possible spectroscopic bio signature of extraterrestrial plants","volume":"5","author":"Seager","year":"2005","journal-title":"Astrobiology"},{"key":"ref_43","unstructured":"Barnes, E.M., Clarke, T.R., Richards, S.E., Colaizzi, P.D., Haberland, J., Kostrzewski, M., Waller, P., Choi, C., Riley, E., and Thompson, T. (2000, January 16\u201319). Coincident Detection of Crop Water Stress, Nitrogen Status and Canopy Density Using Ground-Based Multispectral Data. Bloomington, MN, USA. [CD Rom]."},{"key":"ref_44","unstructured":"R Development Core Team R: A Language and Environment for Statistical Computing. Available online: http:\/\/www.R-project.org\/."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"3079","DOI":"10.1016\/j.rse.2008.03.004","article-title":"Estimation of above- and below-ground biomass across regions of the boreal forest zone using airborne laser","volume":"112","author":"Gobakken","year":"2008","journal-title":"Remote Sens. Environ"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"395","DOI":"10.1093\/forestry\/cpq022","article-title":"Non-parametric prediction and mapping of standing timber volume and biomass in a temperate forest: Application of multiple optical\/ALS-derived predictors","volume":"83","author":"Latifi","year":"2010","journal-title":"Forestry"},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1135","DOI":"10.1080\/01431160500353858","article-title":"Estimating aboveground tree biomass and leaf area index in a mountain birch forest using ASTER satellite data","volume":"27","author":"Heiskanen","year":"2006","journal-title":"Int. J. Remote Sens"},{"key":"ref_48","first-page":"489","article-title":"Kuvioittaisen arvioinnin luotettavuus","volume":"4","author":"Haara","year":"2004","journal-title":"Mets\u00e4tieteenaikakauskirja"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"916","DOI":"10.1139\/x03-266","article-title":"Accuracy of partially visually assessed stand characteristics\u2014A case study of Finnish forest inventory by compartments","volume":"34","author":"Kangas","year":"2004","journal-title":"Can. J. For. Res"},{"key":"ref_50","unstructured":"Montgomery, D.C., Peck, E.A., and Vining, G.G. (2006). Introduction to Linear Regression Analysis, John Wiley & Sons, Inc."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.rse.2007.02.006","article-title":"Investigating RaDAR-LiDAR synergy in a North Carolina pine forest","volume":"110","author":"Nelson","year":"2007","journal-title":"Remote Sens. Environ"},{"key":"ref_52","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_53","first-page":"541","article-title":"Comparing regression methods in estimation of biophysical properties of forest stands from two different inventories using laser scanner data","volume":"94","author":"Gobakken","year":"2004","journal-title":"Remote Sens. Environ"},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"1451","DOI":"10.14358\/PERS.75.12.1451","article-title":"A two stage method to estimate species-specific growing stock by combining ALS data and aerial photographs of known orientation parameters","volume":"75","author":"Suvanto","year":"2009","journal-title":"Photogramm. Eng. Remote Sens"},{"key":"ref_55","first-page":"1","article-title":"Variable selection strategies for nearest neighbor imputation methods used in remote sensing based forest inventory","volume":"38","author":"Temesgen","year":"2012","journal-title":"Can. J. Remote Sens"},{"key":"ref_56","unstructured":"Rana, M.P. (2012). Effect of Field Plot Location on Estimating Tropical Forest Attributes of Nepal. MSc. Thesis,."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"3876","DOI":"10.1016\/j.rse.2008.06.003","article-title":"An analysis of 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_58","unstructured":"Gautam, B.R., Tokola, T., Hamalainen, J., Gunia, M., Peuhkurinen, J., Parviainen, H., Leppanen, V., Kauranne, T., Havia, J., and Norjamaki, I. (2010, January 4\u20136). Integration of Airborne LiDAR, Satellite Imagery and Field Measurements Using A Two-Phase Sampling Method for Forest Biomass Estimation in Tropical Forests."},{"key":"ref_59","first-page":"543","article-title":"Sparse Bayesian estimation of forest stand characteristics from airborne laser scanning","volume":"54","author":"Junttila","year":"2008","journal-title":"For. Sci"},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"6668","DOI":"10.1080\/01431161.2012.693969","article-title":"Evaluation of most similar neighbor and random forest methods for imputing forest inventory variables using data from target and auxiliary stands","volume":"33","author":"Latifi","year":"2012","journal-title":"Int. J. Remote Sens"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"787","DOI":"10.1016\/j.isprsjprs.2011.09.003","article-title":"The role of ground reference data collection in the prediction of stem volume with ALS data in mountain areas","volume":"66","author":"Dalponte","year":"2011","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_62","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_63","doi-asserted-by":"crossref","first-page":"270","DOI":"10.1016\/j.rse.2012.05.016","article-title":"Estimating aboveground carbon stocks of a forest affected by mountain pine beetle in Idaho using lidar and multispectral imagery","volume":"124","author":"Bright","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Fu, A., Sun, G., and Guo, Z. (2009). Estimating forest biomass with GLAS samples and MODIS imagery in northeastern China. Proc. SPIE.","DOI":"10.1117\/12.833596"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"443","DOI":"10.1016\/j.rse.2012.01.025","article-title":"Estimating biomass in Hedmark County, Norway using national forest inventory field plots and airborne laser scanning","volume":"123","author":"Gobakken","year":"2012","journal-title":"Remote Sens. Environ"},{"key":"ref_66","doi-asserted-by":"crossref","unstructured":"Hawbaker, T.J., Keuler, N.S., Lesak, A.A., Gobakken, T., Contrucci, K., and Radeloff, V.C. (2009). Improved estimates of forest vegetation structure and biomass with a LiDAR optimized sampling design. J. Geophy. Res.: Biogeosci.","DOI":"10.1029\/2008JG000870"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"270","DOI":"10.5589\/m09-014","article-title":"Aboveground large tree mass estimation in a coastal forest in British Columbia using plot-level metrics and individual tree detection from lidar","volume":"35","author":"Ferster","year":"2009","journal-title":"Can. J. Remote Sens"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.rse.2008.09.001","article-title":"Effects of different sensors, flying altitudes, and pulse repetition frequencies on forest canopy metrics and biophysical stand properties derived from small-footprint airborne laser data","volume":"113","year":"2009","journal-title":"Remote Sens. Environ"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"135","DOI":"10.3390\/rs4010135","article-title":"Modeling forest structural parameters in the Mediterranean pines of central Spain using QuickBird-2 imagery and Classification and Regression Tree Analysis (CART)","volume":"4","author":"Wulder","year":"2012","journal-title":"Remote Sens"},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"810","DOI":"10.3390\/rs4040810","article-title":"Improved forest biomass and carbon estimations using texture measures from WorldView-2 satellite data","volume":"4","author":"Eckert","year":"2012","journal-title":"Remote Sens"},{"key":"ref_71","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_72","doi-asserted-by":"crossref","first-page":"67","DOI":"10.14214\/sf.a8511","article-title":"Improving satellite image based forest inventory by using a priori site quality information","volume":"31","author":"Tokola","year":"1997","journal-title":"Silva. Fenn"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"156","DOI":"10.1016\/S0034-4257(02)00031-7","article-title":"Simultaneous use of Landsat-TM and IRS-1c WiFS data in estimating large area tree stem volume and aboveground biomass","volume":"82","author":"Tomppo","year":"2002","journal-title":"Remote Sens. Environ"},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"105","DOI":"10.1016\/S0378-1127(99)00059-6","article-title":"Gain to be achieved from stand delineation in Landsat TM image-based estimates of stand volume","volume":"124","author":"Tokola","year":"1999","journal-title":"For. Ecol. Manag"},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"109","DOI":"10.1016\/S0378-1127(99)00278-9","article-title":"Accuracy comparison of various remote sensing data sources in the retrieval of forest stand attributes","volume":"128","author":"Inkinen","year":"2000","journal-title":"For. Ecol. Manag"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"245","DOI":"10.1016\/j.foreco.2004.02.049","article-title":"Estimation of forest stand volumes by Landsat TM imagery and stand-level field-inventory data","volume":"196","author":"Makela","year":"2004","journal-title":"For. Ecol. Manag"},{"key":"ref_77","first-page":"363","article-title":"Kuvioittaisten puustotunnusten ja toimenpide-ehdotusten estimointi k-l\u00e4himm\u00e4n naapurin menetelm\u00e4ll\u00e4LandsatTM-satelliittikuvan, vanhan inventointitiedon ja kuviotason tukiaineiston avulla","volume":"3","year":"2002","journal-title":"Mets\u00e4tieteen Aikakauskirja"},{"key":"ref_78","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 hyper-spectral remote sensing data for forest biomass assessment","volume":"65","author":"Koch","year":"2010","journal-title":"ISPRS J. Photogramm. Remote Sens"},{"key":"ref_79","doi-asserted-by":"crossref","first-page":"830","DOI":"10.3390\/rs4040830","article-title":"LiDAR sampling density for forest resource inventories in Ontario, Canada","volume":"4","author":"Treitz","year":"2012","journal-title":"Remote Sens"},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"2257","DOI":"10.3390\/rs5052257","article-title":"Retrieval of forest aboveground biomass and stem volume with airborne scanning LiDAR","volume":"5","author":"Kankare","year":"2013","journal-title":"Remote Sens"}],"updated-by":[{"DOI":"10.3390\/rs70810242","type":"correction","label":"Correction","source":"publisher","updated":{"date-parts":[[2013,12,27]],"date-time":"2013-12-27T00:00:00Z","timestamp":1388102400000}}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/1\/285\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,4]],"date-time":"2025-08-04T07:53:24Z","timestamp":1754294004000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/6\/1\/285"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,12,27]]},"references-count":80,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2014,1]]}},"alternative-id":["rs6010285"],"URL":"https:\/\/doi.org\/10.3390\/rs6010285","relation":{"correction":[{"id-type":"doi","id":"10.3390\/rs70810242","asserted-by":"object"}]},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2013,12,27]]}}}