{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,18]],"date-time":"2026-03-18T19:07:13Z","timestamp":1773860833517,"version":"3.50.1"},"reference-count":76,"publisher":"MDPI AG","issue":"9","license":[{"start":{"date-parts":[[2017,8,31]],"date-time":"2017-08-31T00:00:00Z","timestamp":1504137600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/100000001","name":"National Science Foundation","doi-asserted-by":"publisher","award":["1226145"],"award-info":[{"award-number":["1226145"]}],"id":[{"id":"10.13039\/100000001","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Joint Fire Sciences","award":["11-1-2-30"],"award-info":[{"award-number":["11-1-2-30"]}]},{"DOI":"10.13039\/100000104","name":"National Aeronautics and Space Administration","doi-asserted-by":"publisher","award":["NNX14AD81G"],"award-info":[{"award-number":["NNX14AD81G"]}],"id":[{"id":"10.13039\/100000104","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Our study objectives were to model the aboveground biomass in a xeric shrub-steppe landscape with airborne light detection and ranging (Lidar) and explore the uncertainty associated with the models we created. We incorporated vegetation vertical structure information obtained from Lidar with ground-measured biomass data, allowing us to scale shrub biomass from small field sites (1 m subplots and 1 ha plots) to a larger landscape. A series of airborne Lidar-derived vegetation metrics were trained and linked with the field-measured biomass in Random Forests (RF) regression models. A Stepwise Multiple Regression (SMR) model was also explored as a comparison. Our results demonstrated that the important predictors from Lidar-derived metrics had a strong correlation with field-measured biomass in the RF regression models with a pseudo R2 of 0.76 and RMSE of 125 g\/m2 for shrub biomass and a pseudo R2 of 0.74 and RMSE of 141 g\/m2 for total biomass, and a weak correlation with field-measured herbaceous biomass. The SMR results were similar but slightly better than RF, explaining 77\u201379% of the variance, with RMSE ranging from 120 to 129 g\/m2 for shrub and total biomass, respectively. We further explored the computational efficiency and relative accuracies of using point cloud and raster Lidar metrics at different resolutions (1 m to 1 ha). Metrics derived from the Lidar point cloud processing led to improved biomass estimates at nearly all resolutions in comparison to raster-derived Lidar metrics. Only at 1 m were the results from the point cloud and raster products nearly equivalent. The best Lidar prediction models of biomass at the plot-level (1 ha) were achieved when Lidar metrics were derived from an average of fine resolution (1 m) metrics to minimize boundary effects and to smooth variability. Overall, both RF and SMR methods explained more than 74% of the variance in biomass, with the most important Lidar variables being associated with vegetation structure and statistical measures of this structure (e.g., standard deviation of height was a strong predictor of biomass). Using our model results, we developed spatially-explicit Lidar estimates of total and shrub biomass across our study site in the Great Basin, U.S.A., for monitoring and planning in this imperiled ecosystem.<\/jats:p>","DOI":"10.3390\/rs9090903","type":"journal-article","created":{"date-parts":[[2017,9,1]],"date-time":"2017-09-01T11:05:24Z","timestamp":1504263924000},"page":"903","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":68,"title":["Lidar Aboveground Vegetation Biomass Estimates in Shrublands: Prediction, Uncertainties and Application to Coarser Scales"],"prefix":"10.3390","volume":"9","author":[{"given":"Aihua","family":"Li","sequence":"first","affiliation":[{"name":"The Department of Geosciences, Boise State University, 1910 University Drive, Boise, ID 83725, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5310-1188","authenticated-orcid":false,"given":"Shital","family":"Dhakal","sequence":"additional","affiliation":[{"name":"The Department of Geosciences, Boise State University, 1910 University Drive, Boise, ID 83725, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2124-7654","authenticated-orcid":false,"given":"Nancy","family":"Glenn","sequence":"additional","affiliation":[{"name":"The Department of Geosciences, Boise State University, 1910 University Drive, Boise, ID 83725, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lucas","family":"Spaete","sequence":"additional","affiliation":[{"name":"The Department of Geosciences, Boise State University, 1910 University Drive, Boise, ID 83725, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Douglas","family":"Shinneman","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, 970 Lusk Street Boise, Boise, ID 83706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4207-3518","authenticated-orcid":false,"given":"David","family":"Pilliod","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, 970 Lusk Street Boise, Boise, ID 83706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3021-1389","authenticated-orcid":false,"given":"Robert","family":"Arkle","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, 970 Lusk Street Boise, Boise, ID 83706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Susan","family":"McIlroy","sequence":"additional","affiliation":[{"name":"U.S. Geological Survey, Forest and Rangeland Ecosystem Science Center, 970 Lusk Street Boise, Boise, ID 83706, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2017,8,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"153","DOI":"10.1016\/S0168-1923(01)00227-1","article-title":"Bowen ratio and closed chamber carbon dioxide flux measurements over sagebrush steppe vegetation","volume":"108","author":"Angell","year":"2001","journal-title":"Agric. For. Meteorol."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"173","DOI":"10.1016\/j.agee.2007.12.007","article-title":"Carbon accumulation and storage in semi-arid sagebrush steppe: Effects of long-term grazing exclusion","volume":"125","author":"Shrestha","year":"2008","journal-title":"Agric. Ecosyst. Environ."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"94","DOI":"10.1111\/j.1744-697X.2011.00213.x","article-title":"Potential forage and biomass production of newly introduced varieties of leucaena (Leucaena leucocephala (Lam.) de Wit.) in Thailand","volume":"57","author":"Rengsirikul","year":"2011","journal-title":"Grassl. Sci."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1016\/j.jaridenv.2010.08.003","article-title":"Carbon pools in an arid shrubland in Chile under natural and afforested conditions","volume":"75","author":"Delpiano","year":"2011","journal-title":"J. Arid Environ."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"140","DOI":"10.1016\/j.rse.2014.11.007","article-title":"Quantifying dwarf shrub biomass in an arid environment: Comparing empirical methods in a high dimensional setting","volume":"158","author":"Zandler","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_6","unstructured":"Barbour, M.G., and Billings, W.D. (2000). North American Terrestrial Vegetation, Cambridge University Press."},{"key":"ref_7","first-page":"145","article-title":"Characteristics of sagebrush habitats and limitations to long-term conservation. Greater sage-grouse: Ecology and conservation of a landscape species and its habitats","volume":"38","author":"Miller","year":"2011","journal-title":"Stud. Avian Biol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"531","DOI":"10.1890\/0012-9615(2001)071[0531:LSCIPS]2.0.CO;2","article-title":"Landscape-scale changes in plant species abundance and biodiversity of a sagebrush steppe over 45 years","volume":"71","author":"Anderson","year":"2011","journal-title":"Ecol. Monogr."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1007\/s00267-014-0362-3","article-title":"Climate change and land management in the rangelands of central Oregon","volume":"55","author":"Creutzburg","year":"2015","journal-title":"Environ. Manag."},{"key":"ref_10","doi-asserted-by":"crossref","unstructured":"Germino, M.J., Chambers, J.C., and Brown, C.S. (2016). Land uses, fire, and invasion: Exotic annual Bromus and human dimensions. Exotic Brome-Grasses in Arid and Semiarid Ecosystems of the Western US: Causes, Consequences, and Management Implications, Springer International Publishing.","DOI":"10.1007\/978-3-319-24930-8"},{"key":"ref_11","unstructured":"Integrated Rangeland Fire Management Strategy Actionable Science Plan Team (2017, August 29). The Integrated Rangeland Fire Management Strategy Actionable Science Plan, Available online: https:\/\/www.fs.fed.us\/rm\/pubs_journals\/2016\/rmrs_2016_berg_k001.pdf."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1007\/BF00389004","article-title":"Small rainfall events: An ecological role in semiarid regions","volume":"53","author":"Sala","year":"1982","journal-title":"Oecologia"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"614","DOI":"10.2111\/07-147.1","article-title":"Point sampling to stratify biomass variability in sagebrush steppe vegetation","volume":"61","author":"Clark","year":"2008","journal-title":"Rangel. Ecol. Manag."},{"key":"ref_14","doi-asserted-by":"crossref","unstructured":"Bonham, C.D. (2013). Measurements for Terrestrial Vegetation, John Wiley & Sons.","DOI":"10.1002\/9781118534540"},{"key":"ref_15","first-page":"38","article-title":"The application of visual estimation procedures for monitoring pasture yield and composition in exclosures and small plots","volume":"28","author":"Waite","year":"1994","journal-title":"Trop. Grassl."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"138","DOI":"10.1016\/j.agrformet.2015.06.005","article-title":"Aboveground biomass estimates of sagebrush using terrestrial and airborne Lidar data in a dryland ecosystem","volume":"213","author":"Li","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2016.07.026","article-title":"High-resolution mapping of aboveground shrub biomass in Arctic tundra using airborne Lidar and imagery","volume":"184","author":"Greaves","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1016\/j.rse.2009.12.018","article-title":"Quantification of live aboveground forest biomass dynamics with Landsat time-series and field inventory data: A comparison of empirical modeling approaches","volume":"114","author":"Powell","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"19","DOI":"10.1641\/0006-3568(2002)052[0019:LRSFES]2.0.CO;2","article-title":"Lidar remote sensing for ecosystem studies","volume":"52","author":"Lefsky","year":"2002","journal-title":"Bioscience"},{"key":"ref_20","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_21","doi-asserted-by":"crossref","first-page":"349","DOI":"10.14358\/PERS.78.4.349","article-title":"Assessment of available rangeland woody plant biomass with a terrestrial LIDAR system","volume":"78","author":"Ku","year":"2012","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"12798","DOI":"10.3390\/s120912798","article-title":"Tree height growth measurement with single-scan airborne, static terrestrial and mobile laser scanning","volume":"12","author":"Lin","year":"2012","journal-title":"Sensors"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"777","DOI":"10.1109\/TGRS.2012.2205003","article-title":"Retrieval of effective leaf area index in heterogeneous forests with terrestrial laser scanning","volume":"51","author":"Zheng","year":"2013","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.rse.2006.02.011","article-title":"Lidar measurement of sagebrush steppe vegetation heights","volume":"102","author":"Streutker","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"407","DOI":"10.1111\/j.1654-109X.2007.tb00440.x","article-title":"Characterization of diverse plant communities in Aspen Parkland rangeland using Lidar data","volume":"10","author":"Su","year":"2007","journal-title":"Appl. Veg. Sci."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"377","DOI":"10.1016\/j.jaridenv.2010.11.005","article-title":"Errors in Lidar-derived shrub height and crown area on sloped terrain","volume":"75","author":"Glenn","year":"2011","journal-title":"J. Arid Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"11","DOI":"10.1016\/j.rse.2007.03.011","article-title":"Integrating LIDAR data and multispectral imagery for enhanced classification of rangeland vegetation: A meta analysis","volume":"111","author":"Bork","year":"2007","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Corchado, E., Kurzy\u0144ski, M., and Wo\u017aniak, M. (2011). A comparative study between two regression methods on Lidar data: A case Study. Hybrid Artificial Intelligent Systems HAIS 2011, Proceedings of the International Conference on Hybrid Artificial Intelligence Systems, Wroc\u0142aw, Poland, 23\u201325 May 2011, Springer. Lecture Notes in Computer Science.","DOI":"10.1007\/978-3-642-21222-2"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.isprsjprs.2014.01.001","article-title":"Above ground biomass estimation in an African tropical forest with Lidar and hyperspectral data","volume":"89","author":"Laurin","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"509","DOI":"10.1080\/13658816.2010.522779","article-title":"Scaling up: Linking field data and remote sensing with a hierarchical model","volume":"25","author":"Wilson","year":"2011","journal-title":"Int. J. Geogr. Inf. Sci."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"2232","DOI":"10.1016\/j.rse.2007.10.009","article-title":"Nearest neighbor imputation of species-level, plot-scale forest structure attributes from Lidar data","volume":"112","author":"Hudak","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"1121","DOI":"10.14358\/PERS.79.12.1121","article-title":"Assessing post-fire regeneration in a Mediterranean mixed forest using Lidar data and artificial neural networks","volume":"79","author":"Debouk","year":"2013","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1023\/A:1010933404324","article-title":"Random Forests","volume":"45","author":"Breiman","year":"2001","journal-title":"Mach. Learn."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"911","DOI":"10.1016\/j.rse.2009.12.004","article-title":"Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data","volume":"114","author":"Breidenbach","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1263","DOI":"10.1016\/j.rse.2010.01.016","article-title":"Imputation of single-tree attributes using airborne laser scanning-based height, intensity, and alpha shape metrics","volume":"114","author":"Vauhkonen","year":"2010","journal-title":"Remote Sens. Environ."},{"key":"ref_36","first-page":"B7","article-title":"Random Forests-Based Feature Selection for Land-Use Classification Using LIDAR Data and Orthoimagery. International Archives of the Photogrammetry","volume":"39","author":"Guan","year":"2012","journal-title":"Remote Sens. Spat. Inf. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"4857","DOI":"10.3390\/rs5104857","article-title":"Single and multi-date Landsat classifications of basalt to support soil survey efforts","volume":"5","author":"Mitchell","year":"2013","journal-title":"Remote Sens."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.rse.2012.07.006","article-title":"Forest biomass estimation from airborne Lidar data using machine learning approaches","volume":"125","author":"Gleason","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"181","DOI":"10.1007\/s10021-005-0054-1","article-title":"Newer classification and regression tree techniques: Bagging and random forests for ecological prediction","volume":"9","author":"Prasad","year":"2006","journal-title":"Ecosystems"},{"key":"ref_40","first-page":"399","article-title":"High density biomass estimation for wetland vegetation using WorldView-2 imagery and random forest regression algorithm","volume":"18","author":"Mutanga","year":"2012","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"98","DOI":"10.1016\/j.rse.2015.04.015","article-title":"Combining airborne hyperspectral and Lidar data across local sites for upscaling shrubland structural information: Lessons for HyspIRI","volume":"167","author":"Mitchell","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"174","DOI":"10.1016\/j.earscirev.2015.05.012","article-title":"Analyzing high resolution topography for advancing the understanding of mass and energy transfer through landscapes: A review","volume":"148","author":"Passalacqua","year":"2015","journal-title":"Earth Sci. Rev."},{"key":"ref_43","first-page":"79","article-title":"Raster vs. Point Cloud Lidar Data Classification","volume":"40","author":"Shaker","year":"2014","journal-title":"Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_44","unstructured":"Western Region Climate Center (WRCC) (2017, June 01). Swan Falls Power House, Idaho, Period of Record General Climate Summary. Available online: http:\/\/www.wrcc.dri.edu\/cgi-bin\/cliMAIN.pl?id8928."},{"key":"ref_45","unstructured":"Anderson, K. (2014). Vegetation Measurement in Sagebrush Steppe Using Terrestrial Laser Scanning. [Master\u2019s Thesis, Idaho State University]."},{"key":"ref_46","unstructured":"U.S. Department of the Interior, Bureau of Land Management, and Boise District Office (2017, June 01). Snake River Birds of Prey National Conservation Area Proposed Resource Management Plan and Final Environmental Impact Statement, Available online: https:\/\/eplanning.blm.gov\/epl-front-office\/projects\/lup\/35553\/41909\/44409\/SRBOPA_NCA_FEIS_V2_Appendices_508.pdf."},{"key":"ref_47","unstructured":"Shinneman, D.J., Arkle, R., Pilliod, D., and Glenn, N.F. (2017, June 01). Quantifying and Predicting Fuels and the Effects of Reduction Treatments along Successional and Invasion Gradients in Sagebrush Habitats, Available online: https:\/\/www.firescience.gov\/projects\/11-1-2-30\/project\/11-1-2-30_final_report.pdf."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"634","DOI":"10.2111\/REM-D-13-00063.1","article-title":"Performance of quantitative sampling methods across gradients of cover in Great Basin plant communities","volume":"66","author":"Pilliod","year":"2013","journal-title":"Rangel. Ecol. Manag."},{"key":"ref_49","doi-asserted-by":"crossref","unstructured":"Spaete, L.P., Glenn, N.F., and Baun, C.W. (2016). 2013 Morley Nelson Snake River Birds of Prey National Conservation Area RapidEye 7 m Landcover Classification, Boise State University. Available online: http:\/\/dx.doi.org\/10.18122\/B21592.","DOI":"10.18122\/B21592"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"233","DOI":"10.1016\/j.rse.2016.02.039","article-title":"Landsat 8 and ICESat-2: Performance and potential synergies for quantifying dryland ecosystem vegetation cover and biomass","volume":"185","author":"Glenn","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1016\/j.rse.2016.06.018","article-title":"The Airborne Snow Observatory: Fusion of scanning Lidar, imaging spectrometer, and physically-based modeling for mapping snow water equivalent and snow albedo","volume":"184","author":"Painter","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"167","DOI":"10.1016\/j.isprsjprs.2012.03.005","article-title":"Classification of savanna tree species, in the Greater Kruger National Park region, by integrating hyperspectral and Lidar data in a Random Forest data mining environment","volume":"69","author":"Naidoo","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"1721","DOI":"10.1016\/j.eswa.2007.01.029","article-title":"Random forests for multiclass classification: Random multinomial logit","volume":"34","author":"Prinzie","year":"2008","journal-title":"Expert Syst. Appl."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"709","DOI":"10.1111\/j.1467-9671.2010.01229.x","article-title":"Modeling the potential distribution of pine forests susceptible to sirex noctilio infestations in Mpumalanga, South Africa","volume":"14","author":"Ismail","year":"2010","journal-title":"Trans. GIS"},{"key":"ref_55","unstructured":"Montgomery, D.C., Peck, E.A., and Vining, G.G. (2015). Introduction to Linear Regression Analysis, John Wiley & Sons."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"393","DOI":"10.1046\/j.1466-822x.2002.00303.x","article-title":"Lidar remote sensing of above-ground biomass in three biomes","volume":"11","author":"Lefsky","year":"2002","journal-title":"Glob. Ecol. Biogeogr."},{"key":"ref_57","unstructured":"Hudak, A., Evans, J.S., Crookstone, N.L., Falkowski, M.J., Steigers, B.K., Taylor, R., and Hemingway, H. (2007, January 13\u201315). Aggregating pixel-level basal area predictions derived from Lidar data to industrial forest stands in North-Central Idaho. Proceedings of the Third Forest Vegetation Simulator Conference, Fort Collins, CO, USA."},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"235","DOI":"10.1080\/02827580902870490","article-title":"The roles of nearest neighbor methods in imputing missing data in forest inventory and monitoring databases","volume":"24","author":"Eskelson","year":"2009","journal-title":"Scand. J. For. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"1","DOI":"10.18637\/jss.v023.i10","article-title":"yaImpute: An R Package for kNN Imputation","volume":"23","author":"Crookston","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1037\/a0016973","article-title":"An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests","volume":"14","author":"Strobl","year":"2009","journal-title":"Psychol. Methods"},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"166","DOI":"10.1016\/j.isprsjprs.2013.12.006","article-title":"Aboveground total and green biomass of dryland shrub derived from terrestrial laser scanning","volume":"88","author":"Olsoy","year":"2014","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"224","DOI":"10.2111\/REM-D-12-00186.1","article-title":"Estimating sagebrush biomass using terrestrial laser scanning","volume":"67","author":"Olsoy","year":"2014","journal-title":"Rangel. Ecol. Manag."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"26","DOI":"10.1016\/j.rse.2015.02.023","article-title":"Estimating aboveground biomass and leaf area of low-stature Arctic shrubs with terrestrial Lidar","volume":"164","author":"Greaves","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Ni-Meister, W., Lee, S., Strahler, A.H., Woodcock, C.E., Schaaf, C., Yao, T., Ranson, K.J., Sun, G., and Blair, J.B. (2010). Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from Lidar remote sensing. J. Geophys. Res. Biogeosci., 115.","DOI":"10.1029\/2009JG000936"},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"317","DOI":"10.1080\/01431161.2010.515267","article-title":"Vegetation and slope effects on accuracy of a Lidar-derived DEM in the sagebrush steppe","volume":"2","author":"Spaete","year":"2011","journal-title":"Remote Sens. Lett."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"521","DOI":"10.14358\/PERS.77.5.521","article-title":"Small-footprint Lidar estimations of sagebrush canopy characteristics","volume":"77","author":"Mitchell","year":"2011","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"341","DOI":"10.1071\/WF06003","article-title":"Estimation of shrub height for fuel-type mapping combining airborne Lidar and simultaneous color infrared ortho imaging","volume":"16","author":"Chuvieco","year":"2007","journal-title":"Int. J. Wildland Fire"},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"710","DOI":"10.1016\/j.biombioe.2012.06.023","article-title":"Estimation of biomass and volume of shrub vegetation using Lidar and spectral data in a Mediterranean environment","volume":"46","author":"Estornell","year":"2012","journal-title":"Biomass Bioenergy"},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"47","DOI":"10.14358\/PERS.72.1.47","article-title":"Mapping sagebrush distribution using fusion of hyperspectral and Lidar classifications","volume":"72","author":"Mundt","year":"2006","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"1182","DOI":"10.1111\/j.1365-2656.2006.01141.x","article-title":"Why do we still use stepwise modelling in ecology and behaviour?","volume":"75","author":"Whittingham","year":"2006","journal-title":"J. Anim. Ecol."},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"2783","DOI":"10.1890\/07-0539.1","article-title":"Random forests for classification in ecology","volume":"88","author":"Cutler","year":"2007","journal-title":"Ecology"},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"311","DOI":"10.2307\/3897313","article-title":"Sampling big sagebrush for phytomass","volume":"30","author":"Uresk","year":"1977","journal-title":"J. Range Manag."},{"key":"ref_73","unstructured":"Brown, J.K. (2017, June 01). Fuel and Fire Behavior Prediction in Big Sagebrush. Available online: https:\/\/www.fs.fed.us\/rm\/pubs_int\/int_rp290.pdf."},{"key":"ref_74","doi-asserted-by":"crossref","first-page":"285","DOI":"10.1016\/j.jaridenv.2007.07.013","article-title":"Testing sagebrush allometric relationships across three fire chronosequences in Wyoming, USA","volume":"72","author":"Cleary","year":"2008","journal-title":"J. Arid Environ."},{"key":"ref_75","doi-asserted-by":"crossref","first-page":"1144","DOI":"10.1002\/jgrg.20088","article-title":"Lidar-derived estimate and uncertainty of carbon sink in successional phases of woody encroachment","volume":"118","author":"Sankey","year":"2013","journal-title":"J. Geophys. Res. Biogeosci."},{"key":"ref_76","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."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/9\/903\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:43:50Z","timestamp":1760208230000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/9\/9\/903"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,8,31]]},"references-count":76,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2017,9]]}},"alternative-id":["rs9090903"],"URL":"https:\/\/doi.org\/10.3390\/rs9090903","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,8,31]]}}}