{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,1]],"date-time":"2026-09-01T13:18:30Z","timestamp":1788268710535,"version":"build-2803163510"},"reference-count":57,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2014,12,24]],"date-time":"2014-12-24T00:00:00Z","timestamp":1419379200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"NASA New Investigator Program","award":["NNX08AR12G"],"award-info":[{"award-number":["NNX08AR12G"]}]},{"name":"United States Forest Service Forest Inventory and Analysis Program","award":["07-JV-11261979-345"],"award-info":[{"award-number":["07-JV-11261979-345"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The United States Forest Service Forest Inventory and Analysis (FIA) Program provides a diverse selection of data used to assess the status of the nation\u2019s forests using sample locations dispersed throughout the country. Airborne laser scanning (ALS) systems are capable of producing accurate measurements of individual tree dimensions and also possess the ability to characterize forest structure in three dimensions. This study investigates the potential of discrete return ALS data for modeling forest aboveground biomass (AGBM) and gross volume (gV) at FIA plot locations in the Malheur National Forest, eastern Oregon utilizing three analysis levels: (1) individual subplot (r = 7.32 m);  (2) plot, comprising four clustered subplots; and (3) hectare plot (r = 56.42 m). A methodology for the creation of three point cloud-based airborne LiDAR metric sets is presented. Models for estimating AGBM and gV based on LiDAR-derived height metrics were built and validated utilizing FIA estimates of AGBM and gV derived using regional allometric equations. Simple linear regression models based on the plot-level analysis out performed subplot-level and hectare-level models, producing R2 values of 0.83 and 0.81 for AGBM and gV, utilizing mean height and the 90th height percentile as predictors, respectively. Similar results were found for multiple regression models, where plot-level analysis produced models with R2 values of 0.87 and 0.88 for AGBM and gV, utilizing multiple height percentile metrics as predictor variables. Results suggest that the current FIA plot design can be used with dense airborne LiDAR data to produce area-based estimates of AGBM and gV, and that the increased spatial scale of hectare plots may be inappropriate for modeling AGBM of gV unless exhaustive tree tallies are available. Overall, this study demonstrates that ALS data can be used to create models that describe the AGBM and gV of Pacific Northwest FIA plots and highlights the potential of estimates derived from ALS data to augment current FIA data collection procedures by providing a temporary intermediate estimation of AGBM and gV for plots with outdated field measurements.<\/jats:p>","DOI":"10.3390\/rs70100229","type":"journal-article","created":{"date-parts":[[2014,12,26]],"date-time":"2014-12-26T05:52:39Z","timestamp":1419573159000},"page":"229-255","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":89,"title":["Modeling Forest Aboveground Biomass and Volume Using Airborne LiDAR Metrics and Forest Inventory and Analysis Data in the Pacific Northwest"],"prefix":"10.3390","volume":"7","author":[{"given":"Ryan","family":"Sheridan","sequence":"first","affiliation":[{"name":"LiDAR Applications for the Study of Ecosystems with Remote Sensing (LASERS) Laboratory, Department of Ecosystem Science and Management, Texas A&M University, 1500 Research Parkway Suite B 217, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sorin","family":"Popescu","sequence":"additional","affiliation":[{"name":"LiDAR Applications for the Study of Ecosystems with Remote Sensing (LASERS) Laboratory, Department of Ecosystem Science and Management, Texas A&M University, 1500 Research Parkway Suite B 217, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Demetrios","family":"Gatziolis","sequence":"additional","affiliation":[{"name":"Pacific Northwest Research Station, United States Forest Service, 620 SW Main Street Suite 400, Portland, OR 97205, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Cristine","family":"Morgan","sequence":"additional","affiliation":[{"name":"Department of Soil and Crop Sciences, Texas A&M University, 545 Heep Center, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nian-Wei","family":"Ku","sequence":"additional","affiliation":[{"name":"LiDAR Applications for the Study of Ecosystems with Remote Sensing (LASERS) Laboratory, Department of Ecosystem Science and Management, Texas A&M University, 1500 Research Parkway Suite B 217, College Station, TX 77843, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2014,12,24]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"88","DOI":"10.1191\/0309133303pp360ra","article-title":"LiDAR remote sensing of forest structure","volume":"27","author":"Lim","year":"2003","journal-title":"Prog. Phys. Geog."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/0034-4257(95)00224-3","article-title":"Estimation of tree heights and stand volume using an airborne LiDAR system","volume":"56","author":"Nilsson","year":"1996","journal-title":"Remote Sens. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1016\/S0034-4257(97)00041-2","article-title":"Estimating timber volume of forest stands using airborne laser scanner data","volume":"61","author":"Naesset","year":"1997","journal-title":"Remote Sens. Environ."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/S0924-2716(97)83000-6","article-title":"Determination of mean tree height of forest stands using airborne laser scanner data","volume":"52","author":"Naesset","year":"1997","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"328","DOI":"10.1016\/S0034-4257(01)00228-0","article-title":"Estimating tree heights and number of stems in young forest stands using airborne laser scanner data","volume":"78","author":"Naesset","year":"2001","journal-title":"Remote Sens. Environ."},{"key":"ref_6","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","author":"Naesset","year":"2002","journal-title":"Remote Sens. Environ."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"71","DOI":"10.1016\/S0168-1699(02)00121-7","article-title":"Estimating plot-level tree heights with LiDAR: Local filtering with a canopy-height based variable window size","volume":"37","author":"Popescu","year":"2002","journal-title":"Comput. Electron. Agric."},{"key":"ref_8","first-page":"419","article-title":"Estimation of tree height and stem volume on plots-using airborne laser scanning","volume":"49","author":"Holmgren","year":"2003","journal-title":"For. Sci."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1978","DOI":"10.1016\/j.rse.2011.04.001","article-title":"Characterizing forest canopy structure with LiDAR composite metrics and machine learning","volume":"115","author":"Zhao","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1016\/j.rse.2013.09.006","article-title":"Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data","volume":"140","author":"Dalponte","year":"2014","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"5154","DOI":"10.1080\/01431161.2013.787501","article-title":"Predicting the spatial pattern of trees by airborne laser scanning","volume":"34","author":"Vauhkonen","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"427","DOI":"10.1016\/j.rse.2005.03.005","article-title":"Mapping forest structure for wildlife habitat analysis using waveform LiDAR: Validation of montane ecosystems","volume":"96","author":"Hyde","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"90","DOI":"10.1890\/070001","article-title":"LiDAR: Shedding new light on habitat characterization and modeling","volume":"6","author":"Vierling","year":"2008","journal-title":"Front. Ecol. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.rse.2012.08.014","article-title":"LiDAR measurements of canopy structure predict spatial distribution of a tropical mature forest primate","volume":"127","author":"Palminteri","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/0378-1127(84)90062-8","article-title":"Woody biomass of forest stands","volume":"8","author":"Cannell","year":"1984","journal-title":"For. Ecol. Manag."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1016\/0034-4257(88)90028-4","article-title":"Estimating forest biomass and volume using airborne laser data","volume":"24","author":"Nelson","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"339","DOI":"10.1016\/S0034-4257(99)00052-8","article-title":"LiDAR remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests","volume":"70","author":"Lefsky","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"543","DOI":"10.1080\/02827580410019472","article-title":"Prediction of tree height, basal area and stem volume in forest stands using airborne laser scanning","volume":"19","author":"Holmgren","year":"2004","journal-title":"Scand. J. For. Res."},{"key":"ref_19","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_20","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_21","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_22","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_23","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.rse.2012.02.023","article-title":"Quantifying aboveground forest carbon pools and fluxes from repeat LiDAR surveys","volume":"123","author":"Hudak","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_24","first-page":"1","article-title":"Prediction of tree biomass in the forest\u2013tundra ecotone using airborne laser scanning","volume":"123","author":"Holmgren","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"5892","DOI":"10.1080\/01431161.2013.798053","article-title":"Development of a national model of Pinus radiata stand volume from LiDAR metrics for New Zealand","volume":"34","author":"Watt","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"121","DOI":"10.1016\/j.rse.2012.11.015","article-title":"A study of forest biomass estimates from LiDAR in the northern temperate forests of New England","volume":"130","author":"Ahmed","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"299","DOI":"10.1016\/j.rse.2012.10.008","article-title":"Model-assisted estimation of change in forest biomass over an 11year period in a sample survey supported by airborne LiDAR: A case study with post-stratification to provide \u201cactivity data\u201d","volume":"128","author":"Naesset","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"451","DOI":"10.1016\/j.rse.2004.02.001","article-title":"Automatic detection of harvested trees and determination of forest growth using airborne laser scanning","volume":"90","author":"Yu","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"968","DOI":"10.1080\/01431161.2012.714504","article-title":"LiDAR-based change detection and change-type determination in urban areas","volume":"34","author":"Teo","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","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":"Forest Ecol. Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"289","DOI":"10.1016\/j.foreco.2008.04.014","article-title":"Sensitivity analysis of fire behavior modeling with LIDAR-derived surface fuel maps","volume":"256","author":"Mutlu","year":"2008","journal-title":"For. Ecol. Manag."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"274","DOI":"10.1016\/j.rse.2007.05.005","article-title":"Mapping surface fuel models using LiDAR and multispectral data fusion for fire behavior","volume":"112","author":"Mutlu","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1136","DOI":"10.1016\/j.foreco.2008.11.022","article-title":"A comparison of LiDAR, radar, and field measurements of canopy height in pine and hardwood forests of southeastern North America","volume":"257","author":"Sexton","year":"2009","journal-title":"For. Ecol. Manag."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1016\/j.rse.2006.07.017","article-title":"Exploring LiDAR\u2013RaDAR synergy\u2014predicting aboveground biomass in a southwestern ponderosa pine forest using LiDAR, SAR and InSAR","volume":"106","author":"Hyde","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"128","DOI":"10.5849\/forsci.12-088","article-title":"Estimating forest stand age from LiDAR-derived predictors and nearest neighbor imputation","volume":"60","author":"Racine","year":"2014","journal-title":"Forest. Sci."},{"key":"ref_36","first-page":"551","article-title":"Fusion of small-footprint LiDAR and multispectral data to estimate plot-level volume and biomass in deciduous and pine forests in Virginia, USA","volume":"50","author":"Popescu","year":"2004","journal-title":"For. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"1","DOI":"10.5589\/m12-049","article-title":"LiDAR plots\u2014A new large-area data collection option: Context, concepts, and case study","volume":"38","author":"Wulder","year":"2012","journal-title":"Can. J. Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"564","DOI":"10.5589\/m03-027","article-title":"Measuring individual tree crown diameter with LiDAR and assessing its influence on estimating forest volume and biomass","volume":"29","author":"Popescu","year":"2003","journal-title":"Can. J. Remote Sens."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"855","DOI":"10.5589\/m04-045","article-title":"Comparison of forest attributes extracted from fine spatial resolution multispectral and LiDAR data","volume":"30","author":"Coops","year":"2004","journal-title":"Can. J. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"415","DOI":"10.1016\/S0034-4257(03)00140-8","article-title":"Identifying species of individual trees using airborne laser scanner","volume":"90","author":"Holmgren","year":"2004","journal-title":"Remote Sens. Environ."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"54","DOI":"10.1016\/j.foreco.2005.03.025","article-title":"Estimating individual tree leaf area in loblolly pine plantations using LiDAR-derived measurements of height and crown dimensions","volume":"213","author":"Roberts","year":"2005","journal-title":"For. Ecol. Manag."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"153","DOI":"10.5589\/m06-005","article-title":"Automated estimation of individual conifer tree height and crown diameter via two-dimensional spatial wavelet analysis of LiDAR data","volume":"32","author":"Falkowski","year":"2006","journal-title":"Can. J. Remote Sens."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"2494","DOI":"10.3390\/rs3112494","article-title":"Airborne Light Detection and Ranging (LiDAR) for individual tree stem location, height, and biomass measurements","volume":"3","author":"Edson","year":"2011","journal-title":"Remote Sens."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"950","DOI":"10.3390\/rs4040950","article-title":"An international comparison of individual tree detection and extraction using airborne laser scanning","volume":"4","author":"Kaartinen","year":"2012","journal-title":"Remote Sens."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1080\/02827580701672147","article-title":"Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia","volume":"22","year":"2007","journal-title":"Scand. J. For. Res."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"589","DOI":"10.14358\/PERS.70.5.589","article-title":"Seeing the trees in the forest: Using LiDAR and multispectral data fusion with local filtering and variable window size for estimating tree height","volume":"70","author":"Popescu","year":"2004","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0378-1127(97)00019-4","article-title":"Biomass equations for sixty-five North American tree species","volume":"97","author":"TerMikaelian","year":"1997","journal-title":"For. Ecol. Manag."},{"key":"ref_48","first-page":"12","article-title":"National-scale biomass estimators for United States tree species","volume":"49","author":"Jenkins","year":"2003","journal-title":"For. Sci."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1016\/j.rse.2008.09.009","article-title":"LiDAR remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers","volume":"113","author":"Zhao","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_50","unstructured":"Zhou, X., and Hemstrom, M.A. Timber Volume and Aboveground Live Tree Biomass Estimations for Landscape Analyses in the Pacific Northwest. Available online: http:\/\/www.fs.fed.us\/pnw\/pubs\/pnw_gtr819.pdf."},{"key":"ref_51","unstructured":"McGaughey, R.J. (2014). FUSION\/LDV: Software for LIDAR Data Analysis and Visualization."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"1095","DOI":"10.1139\/X07-219","article-title":"Assessing effects of laser point density, ground sampling intensity, and field sample plot size on biophysical stand properties derived from airborne laser scanner data","volume":"38","author":"Gobakken","year":"2008","journal-title":"Can. J. For. Res."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"636","DOI":"10.1016\/j.rse.2010.10.008","article-title":"Simulated impact of sample plot size and co-registration error on the accuracy and uncertainty of LiDAR-derived estimates of forest stand biomass","volume":"115","author":"Frazer","year":"2011","journal-title":"Remote Sens. Environ."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TAC.1974.1100705","article-title":"A new look at the statistical model identification","volume":"19","author":"Akaike","year":"1974","journal-title":"IEEE Trans. Autom. Control"},{"key":"ref_55","unstructured":"Sheskin, D.J. (2007). Handbook of Parametric and Nonparametric Statistical Procedures, Chapman & Hall\/CRC. [4th ed.]."},{"key":"ref_56","unstructured":"Myers, R.H. (1990). Classical and Modern Regression with Applications, PWS-Kent."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"453","DOI":"10.1016\/j.rse.2005.04.001","article-title":"Estimating forest growth using canopy metrics derived from airborne laser scanner data","volume":"96","author":"Nasset","year":"2005","journal-title":"Remote Sens. Environ."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/1\/229\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T11:22:52Z","timestamp":1770376972000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/7\/1\/229"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2014,12,24]]},"references-count":57,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2015,1]]}},"alternative-id":["rs7010229"],"URL":"https:\/\/doi.org\/10.3390\/rs70100229","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2014,12,24]]}}}