{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,10]],"date-time":"2026-04-10T05:21:22Z","timestamp":1775798482351,"version":"3.50.1"},"reference-count":83,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2022,12,27]],"date-time":"2022-12-27T00:00:00Z","timestamp":1672099200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"USDI Bureau of Land Management"},{"name":"Oregon State Office"},{"name":"USDA Forest Service"},{"name":"Pacific Northwest Research Station"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>We developed new measures of structural complexity using single point terrestrial laser scanning (TLS) point clouds. These metrics are depth, openness, and isovist. Depth is a three-dimensional, radial measure of the visible distance in all directions from plot center. Openness is the percent of scan pulses in the near-omnidirectional view without a return. Isovists are a measurement of the area visible from the scan location, a quantified measurement of the viewshed within the forest canopy. 243 scans were acquired in 27 forested stands in the Pacific Northwest region of the United States, in different ecoregions representing a broad gradient in structural complexity. All stands were designated natural areas with little to no human perturbations. We created \u201cstructural signatures\u201d from depth and openness metrics that can be used to qualitatively visualize differences in forest structures and quantitively distinguish the structural composition of a forest at differing height strata. In most cases, the structural signatures of stands were effective at providing statistically significant metrics differentiating forests from various ecoregions and growth patterns. Isovists were less effective at differentiating between forested stands across multiple ecoregions, but they still quantify the ecological important metric of occlusion. These new metrics appear to capture the structural complexity of forests with a high level of precision and low observer bias and have great potential for quantifying structural change to forest ecosystems, quantifying effects of forest management activities, and describing habitat for organisms. Our measures of structure can be used to ground truth data obtained from aerial lidar to develop models estimating forest structure.<\/jats:p>","DOI":"10.3390\/rs15010145","type":"journal-article","created":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T05:30:27Z","timestamp":1672205427000},"page":"145","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":15,"title":["New Structural Complexity Metrics for Forests from Single Terrestrial Lidar Scans"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8700-3076","authenticated-orcid":false,"given":"Jonathan L.","family":"Batchelor","sequence":"first","affiliation":[{"name":"School of Environmental and Forest Sciences, University of Washington, Seattle, WA 98195, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6031-957X","authenticated-orcid":false,"given":"Todd M.","family":"Wilson","sequence":"additional","affiliation":[{"name":"USDA Forest Service, Pacific Northwest Research Station, Corvallis, OR 97331, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2989-5309","authenticated-orcid":false,"given":"Michael J.","family":"Olsen","sequence":"additional","affiliation":[{"name":"School of Civil and Construction Engineering, Oregon State University, Corvallis, OR 97331, USA"}]},{"given":"William J.","family":"Ripple","sequence":"additional","affiliation":[{"name":"Department of Forest Ecosystems and Society, Oregon State University, Corvallis, OR 97331, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,12,27]]},"reference":[{"key":"ref_1","unstructured":"Lindenmayer, D.B., and Franklin, J.F. (2002). Conserving Forest Biodiversity: A Comprehensive Multiscaled Approach, Island Press."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Carey, A.B. (2007). AIMing for Healthy Forests: Active, Intentional Management for Multiple Values, General Technical Report PNW-GTR-721.","DOI":"10.2737\/PNW-GTR-721"},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Shugart, H., Saatchi, S., and Hall, F. (2010). Importance of Structure and Its Measurement in Quantifying Function of Forest Ecosystems. J. Geophys. Res. Biogeosci., 115.","DOI":"10.1029\/2009JG000993"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/S0065-2504(08)60179-8","article-title":"Sunflecks and Their Importance to Forest Understorey Plants","volume":"18","author":"Chazdon","year":"1988","journal-title":"Adv. Ecol. Res."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1890\/1051-0761(1997)007[0564:FSAPAI]2.0.CO;2","article-title":"Forest Structure and Prey Abundance in Foraging Areas of Northern Goshawks","volume":"7","author":"Beier","year":"1997","journal-title":"Ecol. Appl."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"253","DOI":"10.1016\/j.biocon.2005.01.033","article-title":"The Role of Forest Structure, Fragment Size and Corridors in Maintaining Small Mammal Abundance and Diversity in an Atlantic Forest Landscape","volume":"124","author":"Pardini","year":"2005","journal-title":"Biol. Conserv."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.agrformet.2012.03.011","article-title":"Influence of Canopy Structure and Direct Beam Solar Irradiance on Snowmelt Rates in a Mixed Conifer Forest","volume":"161","author":"Musselman","year":"2012","journal-title":"Agric. For. Meteorol."},{"key":"ref_8","first-page":"125","article-title":"A Rapid Forest Assessment Method for Multiparty Monitoring across Landscapes","volume":"114","author":"Davis","year":"2016","journal-title":"J. For."},{"key":"ref_9","unstructured":"Everett, R.L., and Leader, A.T. (1994). Eastside Forest Ecosystem Health Assessment, General Technical Report PNW-GTR-330."},{"key":"ref_10","unstructured":"Massie, M. (2014). Assessment of the Vulnerability of Oregon and Washington\u2019s Natural Areas to Climate Change. [Master\u2019s Thesis, Oregon State University]."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Rapp, V. (2008). Northwest Forest Plan\u2014The First 10 Years (1994\u20132003): First-Decade Results of the Northwest Forest Plan, General Technical Report PNW-GTR-720.","DOI":"10.2737\/PNW-GTR-720"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1016\/S0378-1127(97)00249-1","article-title":"Development of Old-Growth Structure and Timber Volume Growth Trends in Maturing Douglas-Fir Stands","volume":"104","author":"Acker","year":"1998","journal-title":"For. Ecol. Manag."},{"key":"ref_13","first-page":"203","article-title":"Models for Mapping Potential Habitat at Landscape Scales: An Example Using Northern Spotted Owls","volume":"48","author":"McComb","year":"2002","journal-title":"For. Sci."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.foreco.2005.08.034","article-title":"Forest and Woodland Stand Structural Complexity: Its Definition and Measurement","volume":"218","author":"McElhinny","year":"2005","journal-title":"For. Ecol. Manag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1105","DOI":"10.1139\/x01-033","article-title":"Introduction and Evaluation of Possible Indices of Stand Structural Diversity","volume":"31","author":"Staudhammer","year":"2001","journal-title":"Can. J. For. Res."},{"key":"ref_16","unstructured":"Tuchmann, E.T., and Connaughton, K.P. (1998). The Northwest Forest Plan: A Report to the President and Congress, DIANE Publishing."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1093\/forestry\/75.3.305","article-title":"Approaches to Quantifying Forest Structures","volume":"75","author":"Pommerening","year":"2002","journal-title":"Forestry"},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"325","DOI":"10.5194\/isprs-annals-IV-2-W5-325-2019","article-title":"Comparison of Forest Structure Metrics Derived from UAV Lidar and ALS Data","volume":"4","author":"Bruggisser","year":"2019","journal-title":"ISPRS Ann. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"40","DOI":"10.1016\/j.agrformet.2015.04.013","article-title":"Novel Forest Structure Metrics from Airborne LiDAR Data for Improved Snow Interception Estimation","volume":"208","author":"Moeser","year":"2015","journal-title":"Agric. For. Meteorol."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.12942\/lrlr-2009-1","article-title":"Landscape Metrics and Indices: An Overview of Their Use in Landscape Research","volume":"3","author":"Uuemaa","year":"2009","journal-title":"Living Rev. Landsc. Res."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Frey, J., Joa, B., Schraml, U., and Koch, B. (2019). Same Viewpoint Different Perspectives\u2014A Comparison of Expert Ratings with a TLS Derived Forest Stand Structural Complexity Index. Remote Sens., 11.","DOI":"10.3390\/rs11091137"},{"key":"ref_22","first-page":"606","article-title":"Comparison of Methods for Estimating Forest Overstory Cover","volume":"18","author":"Vales","year":"1988","journal-title":"I. Observer Effects. Can. J. For. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"117484","DOI":"10.1016\/j.foreco.2019.117484","article-title":"On Promoting the Use of Lidar Systems in Forest Ecosystem Research","volume":"450","author":"Beland","year":"2019","journal-title":"For. Ecol. Manag."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"573","DOI":"10.1007\/s11056-019-09754-5","article-title":"Monitoring Forest Structure to Guide Adaptive Management of Forest Restoration: A Review of Remote Sensing Approaches","volume":"51","author":"Camarretta","year":"2020","journal-title":"New For."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"196","DOI":"10.1016\/j.rse.2012.02.001","article-title":"Lidar Sampling for Large-Area Forest Characterization: A Review","volume":"121","author":"Wulder","year":"2012","journal-title":"Remote Sens. Environ."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"39","DOI":"10.1016\/j.rse.2013.02.018","article-title":"Investigating Assumptions of Crown Archetypes for Modelling LiDAR Returns","volume":"134","author":"Calders","year":"2013","journal-title":"Remote Sens. Environ."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1016\/S0034-4257(03)00139-1","article-title":"Characterizing Vertical Forest Structure Using Small-Footprint Airborne LiDAR","volume":"87","author":"Zimble","year":"2003","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1016\/j.rse.2014.09.025","article-title":"The Evolution of Mapping Habitat for Northern Spotted Owls (Strix Occidentalis Caurina): A Comparison of Photo-Interpreted, Landsat-Based, and Lidar-Based Habitat Maps","volume":"156","author":"Ackers","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"112477","DOI":"10.1016\/j.rse.2021.112477","article-title":"Modelling Lidar-Derived Estimates of Forest Attributes over Space and Time: A Review of Approaches and Future Trends","volume":"260","author":"Coops","year":"2021","journal-title":"Remote Sens. Environ."},{"key":"ref_30","doi-asserted-by":"crossref","unstructured":"Lister, A.J., Andersen, H., Frescino, T., Gatziolis, D., Healey, S., Heath, L.S., Liknes, G.C., McRoberts, R., Moisen, G.G., and Nelson, M. (2020). Use of Remote Sensing Data to Improve the Efficiency of National Forest Inventories: A Case Study from the United States National Forest Inventory. Forests, 11.","DOI":"10.3390\/f11121364"},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"1251","DOI":"10.1139\/cjfr-2018-0196","article-title":"Applications of the United States Forest Inventory and Analysis Dataset: A Review and Future Directions","volume":"48","author":"Tinkham","year":"2018","journal-title":"Can. J. For. Res."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"330","DOI":"10.1016\/j.rse.2018.06.023","article-title":"Quantifying Understory Vegetation Density Using Small-Footprint Airborne Lidar","volume":"215","author":"Campbell","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1007\/s00468-010-0452-7","article-title":"Comparing Canopy Metrics Derived from Terrestrial and Airborne Laser Scanning in a Douglas-Fir Dominated Forest Stand","volume":"24","author":"Hilker","year":"2010","journal-title":"Trees"},{"key":"ref_34","unstructured":"Ruiz, L.\u00c1., Crespo-Peremarch, P., and Torralba, J. (2021, January 24\u201325). Modelling Canopy Fuel Properties and Understory Vegetation with Full-Waveform LiDAR. Proceedings of the International Conference on Smart Geoinformatics Applications (ICSGA 2021), Phuket, Thailand."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"112102","DOI":"10.1016\/j.rse.2020.112102","article-title":"Terrestrial Laser Scanning in Forest Ecology: Expanding the Horizon","volume":"251","author":"Calders","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_36","first-page":"67","article-title":"Detailed Stem Measurements of Standing Trees from Ground-Based Scanning Lidar","volume":"52","author":"Henning","year":"2006","journal-title":"For. Sci."},{"key":"ref_37","doi-asserted-by":"crossref","unstructured":"Palace, M., Sullivan, F.B., Ducey, M., and Herrick, C. (2016). Estimating Tropical Forest Structure Using a Terrestrial Lidar. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0154115"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"676","DOI":"10.1071\/WF07138","article-title":"Ground-Based LIDAR: A Novel Approach to Quantify Fine-Scale Fuelbed Characteristics","volume":"18","author":"Loudermilk","year":"2009","journal-title":"Int. J. Wildland Fire"},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"117945","DOI":"10.1016\/j.foreco.2020.117945","article-title":"Coupling Terrestrial Laser Scanning with 3D Fuel Biomass Sampling for Advancing Wildland Fuels Characterization","volume":"462","author":"Rowell","year":"2020","journal-title":"For. Ecol. Manag."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"119037","DOI":"10.1016\/j.foreco.2021.119037","article-title":"Detecting the Effects of Logging and Wildfire on Forest Fuel Structure Using Terrestrial Laser Scanning (TLS)","volume":"488","author":"Wilson","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"263","DOI":"10.1111\/2041-210X.12157","article-title":"Creating Vegetation Density Profiles for a Diverse Range of Ecological Habitats Using Terrestrial Laser Scanning","volume":"5","author":"Ashcroft","year":"2014","journal-title":"Methods Ecol. Evol."},{"key":"ref_42","unstructured":"Kazakova, A.N. (2014). Quantifying Vertical and Horizontal Stand Structure Using Terrestrial LiDAR in Pacific Northwest Forests. [Master\u2019s Thesis, University of Washington]."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"74","DOI":"10.1093\/biosci\/biu189","article-title":"Fearscapes: Mapping Functional Properties of Cover for Prey with Terrestrial LiDAR","volume":"65","author":"Olsoy","year":"2015","journal-title":"BioScience"},{"key":"ref_44","doi-asserted-by":"crossref","unstructured":"Shokirov, S., Levick, S.R., Jucker, T., Yeoh, P., and Youngentob, K. (October, January 26). Comparison of TLS and ULS Data for Wildlife Habitat Assessments in Temperate Woodlands. Proceedings of the IGARSS 2020\u20142020 IEEE International Geoscience and Remote Sensing Symposium, Online.","DOI":"10.1109\/IGARSS39084.2020.9323451"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"111836","DOI":"10.1016\/j.rse.2020.111836","article-title":"Mitigating Occlusion Effects in Leaf Area Density Estimates from Terrestrial LiDAR through a Specific Kriging Method","volume":"245","author":"Soma","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1186\/s40663-019-0203-1","article-title":"Quantification of Occlusions Influencing the Tree Stem Curve Retrieving from Single-Scan Terrestrial Laser Scanning Data","volume":"6","author":"Wan","year":"2019","journal-title":"For. Ecosyst."},{"key":"ref_47","unstructured":"Litkey, P., Liang, X., Kaartinen, H., Hyypp\u00e4, J., Kukko, A., Holopainen, M., Hill, R., Rosette, J., and Su\u00e1rez, J. (2008, January 17\u201319). Single-Scan TLS Methods for Forest Parameter Retrieval. Proceedings of the SilviLaser, Edinburgh, UK."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"3923","DOI":"10.3390\/f6113923","article-title":"Detecting Stems in Dense and Homogeneous Forest Using Single-Scan TLS","volume":"6","author":"Xia","year":"2015","journal-title":"Forests"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"101484","DOI":"10.1016\/j.mex.2021.101484","article-title":"A Simplified and Affordable Approach to Forest Monitoring Using Single Terrestrial Laser Scans and Transect Sampling","volume":"8","author":"Pokswinski","year":"2021","journal-title":"MethodsX"},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1","DOI":"10.3390\/rs4010001","article-title":"Retrieving Forest Inventory Variables with Terrestrial Laser Scanning (TLS) in Urban Heterogeneous Forest","volume":"4","author":"Moskal","year":"2011","journal-title":"Remote Sens."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"20304","DOI":"10.3390\/s141120304","article-title":"Terrestrial Laser Scanning for Vegetation Sampling","volume":"14","author":"Richardson","year":"2014","journal-title":"Sensors"},{"key":"ref_52","doi-asserted-by":"crossref","unstructured":"Kato, A., Moskal, L.M., Batchelor, J.L., Thau, D., and Hudak, A.T. (2019). Relationships between Satellite-Based Spectral Burned Ratios and Terrestrial Laser Scanning. Forests, 10.","DOI":"10.3390\/f10050444"},{"key":"ref_53","doi-asserted-by":"crossref","unstructured":"Gallagher, M.R., Maxwell, A.E., Guill\u00e9n, L.A., Everland, A., Loudermilk, E.L., and Skowronski, N.S. (2021). Estimation of Plot-Level Burn Severity Using Terrestrial Laser Scanning. Remote Sens., 13.","DOI":"10.3390\/rs13204168"},{"key":"ref_54","first-page":"1","article-title":"Discriminating Forest Leaf and Wood Components in TLS Point Clouds at Single-Scan Level Using Derived Geometric Quantities","volume":"60","author":"Tan","year":"2021","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"119118","DOI":"10.1016\/j.foreco.2021.119118","article-title":"Traditional Field Metrics and Terrestrial LiDAR Predict Plant Richness in Southern Pine Forests","volume":"491","author":"Anderson","year":"2021","journal-title":"For. Ecol. Manag."},{"key":"ref_56","doi-asserted-by":"crossref","unstructured":"Wallace, L., Hillman, S., Hally, B., Taneja, R., White, A., and McGlade, J. (2022). Terrestrial Laser Scanning: An Operational Tool for Fuel Hazard Mapping?. Fire, 5.","DOI":"10.3390\/fire5040085"},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1111\/tgis.12022","article-title":"Airborne LiDAR and Terrestrial Laser Scanning Derived Vegetation Obstruction Factors for Visibility Models","volume":"18","author":"Murgoitio","year":"2014","journal-title":"Trans. GIS"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1111\/j.1467-8306.1987.tb00149.x","article-title":"Ecoregions of the Conterminous United States","volume":"77","author":"Omernik","year":"1987","journal-title":"Ann. Assoc. Am. Geogr."},{"key":"ref_59","unstructured":"Wilson, T.M. (2015, March 28). Pacific Northwest Interagency Natural Areas Network. Available online: http:\/\/www.fsl.orst.edu\/rna\/index.html."},{"key":"ref_60","unstructured":"(2015, March 30). LEMMA Landscape Ecology, Modeling, Mapping & Analysis Home Page. Available online: http:\/\/lemma.forestry.oregonstate.edu\/."},{"key":"ref_61","unstructured":"ESRI (2014). ArcGIS Desktop, ESRI. Version 10."},{"key":"ref_62","unstructured":"(2015, March 31). FARO Scene [Computer Software]; Version 5.3; FARO: Lake Mary, FL, USA. Available online: http:\/\/www.faro.com."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s00340-013-5447-9","article-title":"A Method of Background Noise Reduction in Lidar Data","volume":"113","author":"Cao","year":"2013","journal-title":"Appl. Phys. B"},{"key":"ref_64","doi-asserted-by":"crossref","unstructured":"Stovall, A.E.L., and Atkins, J.W. (2021). Assessing Low-Cost Terrestrial Laser Scanners for Deriving Forest Structure Parameters. Preprints, 2021070690.","DOI":"10.20944\/preprints202107.0690.v1"},{"key":"ref_65","unstructured":"Olsen, M.J., Ponto, K., Kimball, J., Seracini, M., and Kuester, F. (2010, January 6\u20139). 2D Open-Source Editing Techniques for 3D Laser Scans. Proceedings of the 38th Annual Conference on Computer Applications and Quantitative Methods in Archaeology, Granada, Spain."},{"key":"ref_66","unstructured":"(2015, March 30). Mathworks MATLAB R2015a [Computer Program]. Available online: HTTP:\/\/www.mathworks.Com\/products\/matlab\/."},{"key":"ref_67","first-page":"1","article-title":"FactoMineR: An R Package for Multivariate Analysis","volume":"25","author":"Josse","year":"2008","journal-title":"J. Stat. Softw."},{"key":"ref_68","first-page":"1","article-title":"Tukey\u2019s Honestly Significant Difference (HSD) Test","volume":"3","author":"Abdi","year":"2010","journal-title":"Encycl. Res. Des."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"624","DOI":"10.1111\/2041-210X.12902","article-title":"A Call for Viewshed Ecology: Advancing Our Understanding of the Ecology of Information through Viewshed Analysis","volume":"9","author":"Aben","year":"2018","journal-title":"Methods Ecol. Evol."},{"key":"ref_70","doi-asserted-by":"crossref","unstructured":"Davies, A.B., Tambling, C.J., Kerley, G.I., and Asner, G.P. (2016). Effects of Vegetation Structure on the Location of Lion Kill Sites in African Thicket. PLoS ONE, 11.","DOI":"10.1371\/journal.pone.0149098"},{"key":"ref_71","doi-asserted-by":"crossref","first-page":"1736","DOI":"10.1139\/z03-174","article-title":"Habitat Preference of Canada Lynx through a Cycle in Snowshoe Hare Abundance","volume":"81","author":"Mowat","year":"2003","journal-title":"Can. J. Zool."},{"key":"ref_72","doi-asserted-by":"crossref","first-page":"360","DOI":"10.22621\/cfn.v117i3.738","article-title":"A Review of the Canada Lynx, Lynx Canadensis, in Canada","volume":"117","author":"Poole","year":"2003","journal-title":"Can. Field-Nat."},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1002\/wsb.1018","article-title":"Predicting Forest Understory Habitat for Canada Lynx Using LIDAR Data","volume":"43","author":"Fekety","year":"2019","journal-title":"Wildl. Soc. Bull."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Galluzzi, M., Puletti, N., Armanini, M., Chirichella, R., and Mustoni, A. (2022). Mobile Laser Scanner Understory Characterization: An Exploratory Study on Hazel Grouse in Italian Alps. bioRxiv.","DOI":"10.1101\/2022.04.26.489487"},{"key":"ref_75","unstructured":"Burgett, S., Rachlow, J., and Stein, R. (2022, December 16). Unexpected Properties of Habitat Altered by Ecosystem Engineers: A Pygmy Rabbit Case Study. Available online: https:\/\/scholarworks.boisestate.edu\/icur\/2021\/poster_session\/12\/."},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"733","DOI":"10.1111\/2041-210X.13385","article-title":"Viewshed3d: An R Package for Quantifying 3D Visibility Using Terrestrial Lidar Data","volume":"11","author":"Lecigne","year":"2020","journal-title":"Methods Ecol. Evol."},{"key":"ref_77","doi-asserted-by":"crossref","unstructured":"Fan, G., Nan, L., Dong, Y., Su, X., and Chen, F. (2020). AdQSM: A New Method for Estimating Above-Ground Biomass from TLS Point Clouds. Remote Sens., 12.","DOI":"10.3390\/rs12183089"},{"key":"ref_78","doi-asserted-by":"crossref","first-page":"1274","DOI":"10.3390\/f6041274","article-title":"Non Destructive Method for Biomass Prediction Combining TLS Derived Tree Volume and Wood Density","volume":"6","author":"Hackenberg","year":"2015","journal-title":"Forests"},{"key":"ref_79","first-page":"91","article-title":"Biomass Estimation of Individual Trees Using Stem and Crown Diameter TLS Measurements","volume":"3812","author":"Holopainen","year":"2011","journal-title":"ISPRS\u2014Int. Arch. Photogramm. Remote Sens. Spat. Inf. Sci."},{"key":"ref_80","doi-asserted-by":"crossref","first-page":"77","DOI":"10.1016\/j.rse.2017.03.017","article-title":"Area-Based vs Tree-Centric Approaches to Mapping Forest Carbon in Southeast Asian Forests from Airborne Laser Scanning Data","volume":"194","author":"Coomes","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_81","doi-asserted-by":"crossref","first-page":"111779","DOI":"10.1016\/j.rse.2020.111779","article-title":"Biomass Estimation from Simulated GEDI, ICESat-2 and NISAR across Environmental Gradients in Sonoma County, California","volume":"242","author":"Duncanson","year":"2020","journal-title":"Remote Sens. Environ."},{"key":"ref_82","doi-asserted-by":"crossref","first-page":"741","DOI":"10.1016\/j.rse.2017.09.027","article-title":"Large-Area Hybrid Estimation of Aboveground Biomass in Interior Alaska Using Airborne Laser Scanning Data","volume":"204","author":"Ene","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_83","doi-asserted-by":"crossref","first-page":"1266","DOI":"10.1080\/15481603.2022.2103069","article-title":"Filtering Ground Noise from LiDAR Returns Produces Inferior Models of Forest Aboveground Biomass in Heterogenous Landscapes","volume":"59","author":"Mahoney","year":"2022","journal-title":"GISci. 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