{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,7]],"date-time":"2026-07-07T05:28:02Z","timestamp":1783402082674,"version":"3.54.6"},"reference-count":48,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2018,2,24]],"date-time":"2018-02-24T00:00:00Z","timestamp":1519430400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The increasing availability of highly detailed three-dimensional remotely-sensed data depicting forests, including airborne laser scanning (ALS) and digital aerial photogrammetric (DAP) approaches, provides a means for improving stand dynamics information. The availability of data from ALS and DAP has stimulated attempts to link these datasets with conventional forestry growth and yield models. In this study, we demonstrated an approach whereby two three-dimensional point cloud datasets (one from ALS and one from DAP), acquired over the same forest stands, at two points in time (circa 2008 and 2015), were used to derive forest inventory information. The area-based approach (ABA) was used to predict top height (H), basal area (BA), total volume (V), and stem density (N) for Time 1 and Time 2 (T1, T2). We assigned individual yield curves to 20 \u00d7 20 m grid cells for two scenarios. The first scenario used T1 estimates only (approach 1, single date), while the second scenario combined T1 and T2 estimates (approach 2, multi-date). Yield curves were matched by comparing the predicted cell-level attributes with a yield curve template database generated using an existing growth simulator. Results indicated that the yield curves using the multi-date data of approach 2 were matched with slightly higher accuracy; however, projections derived using approach 1 and 2 were not significantly different. The accuracy of curve matching was dependent on the ABA prediction error. The relative root mean squared error of curve matching in approach 2 for H, BA, V, and N, was 18.4, 11.5, 25.6, and 27.53% for observed (plot) data, and 13.2, 44.6, 50.4 and 112.3% for predicted data, respectively. The approach presented in this study provides additional detail on sub-stand level growth projections that enhances the information available to inform long-term, sustainable forest planning and management.<\/jats:p>","DOI":"10.3390\/rs10020347","type":"journal-article","created":{"date-parts":[[2018,2,27]],"date-time":"2018-02-27T04:20:47Z","timestamp":1519705247000},"page":"347","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":60,"title":["Combining Multi-Date Airborne Laser Scanning and Digital Aerial Photogrammetric Data for Forest Growth and Yield Modelling"],"prefix":"10.3390","volume":"10","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-5841-6530","authenticated-orcid":false,"given":"Piotr","family":"Tompalski","sequence":"first","affiliation":[{"name":"Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0151-9037","authenticated-orcid":false,"given":"Nicholas","family":"Coops","sequence":"additional","affiliation":[{"name":"Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5479-557X","authenticated-orcid":false,"given":"Peter","family":"Marshall","sequence":"additional","affiliation":[{"name":"Faculty of Forestry, University of British Columbia, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-4674-0373","authenticated-orcid":false,"given":"Joanne","family":"White","sequence":"additional","affiliation":[{"name":"Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6942-1896","authenticated-orcid":false,"given":"Michael","family":"Wulder","sequence":"additional","affiliation":[{"name":"Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, 506 West Burnside Road, Victoria, BC V8Z 1M5, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Todd","family":"Bailey","sequence":"additional","affiliation":[{"name":"West Fraser\u2014Slave Lake, P.O. Box 1790, Slave Lake, AB T0G 2A0, Canada"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2018,2,24]]},"reference":[{"key":"ref_1","unstructured":"Avery, T.E., and Burkhart, H. (2002). Forest Measurements, McGraw-Hill."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Pretzsch, H. (2009). Forest Dynamics, Growth and Yield, Springer.","DOI":"10.1007\/978-3-540-88307-4"},{"key":"ref_3","unstructured":"(2015, June 10). Ministry of Forest Lands and Natural Resource Operations Growth and Yield Modelling, Available online: https:\/\/www.for.gov.bc.ca\/hts\/growth\/tipsy\/tipsy_description.html."},{"key":"ref_4","unstructured":"Huang, S., Meng, S.X., and Yang, Y. (2017, December 04). A Growth and Yield Projection System (GYPSY) for Natural and Post-Harvest Stands in Alberta, Available online: https:\/\/www.agric.gov.ab.ca\/app21\/forestrypage?cat1=Forest%20Management&cat2=Growth%20%26%20Yield."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"722","DOI":"10.5558\/tfc2013-132","article-title":"A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach","volume":"89","author":"White","year":"2013","journal-title":"For. Chron."},{"key":"ref_6","doi-asserted-by":"crossref","unstructured":"Maltamo, M., N\u00e6sset, E., and Vauhkonen, J. (2014). Forestry Applications of Airborne Laser Scanning, Springer.","DOI":"10.1007\/978-94-017-8663-8"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"619","DOI":"10.1080\/07038992.2016.1207484","article-title":"Remote Sensing Technologies for Enhancing Forest Inventories: A Review","volume":"42","author":"White","year":"2016","journal-title":"Can. J. Remote Sens."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1007\/s00468-006-0119-6","article-title":"Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR","volume":"21","author":"Coops","year":"2007","journal-title":"Trees Struct. Funct."},{"key":"ref_9","first-page":"426","article-title":"Parametric vs. nonparametric LiDAR models for operational forest inventory in boreal Ontario","volume":"39","author":"Penner","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_10","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_11","first-page":"27","article-title":"Detecting and estimating attributes for single trees using laser scanner","volume":"16","author":"Inkinen","year":"1999","journal-title":"Photogramm. J. Finland"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"4163","DOI":"10.3390\/rs5094163","article-title":"Delineating Individual Trees from Lidar Data: A Comparison of Vector- and Raster-based Segmentation Approaches","volume":"5","author":"Jakubowski","year":"2013","journal-title":"Remote Sens."},{"key":"ref_13","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_14","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1080\/02827581.2014.961954","article-title":"Comparing biophysical forest characteristics estimated from photogrammetric matching of aerial images and airborne laser scanning data","volume":"30","author":"Gobakken","year":"2015","journal-title":"Scand. J. For. Res."},{"key":"ref_15","first-page":"111","article-title":"Using semi-global matching point clouds to estimate growing stock at the plot and stand levels: Application for a broadleaf-dominated forest in central Europe","volume":"45","author":"Stepper","year":"2015","journal-title":"Can. J. Remote Sens."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Balenovi\u0107, I., Simic Milas, A., and Marjanovi\u0107, H. (2017). A Comparison of Stand-Level Volume Estimates from Image-Based Canopy Height Models of Different Spatial Resolutions. Remote Sens., 9.","DOI":"10.3390\/rs9030205"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1080\/02827581.2016.1186727","article-title":"Assessing 3D point clouds from aerial photographs for species-specific forest inventories inventories","volume":"32","author":"Puliti","year":"2017","journal-title":"Scand. J. For. Res."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"15933","DOI":"10.3390\/rs71215809","article-title":"Comparison of Laser and Stereo Optical, SAR and InSAR Point Clouds from Air- and Space-Borne Sources in the Retrieval of Forest Inventory Attributes","volume":"7","author":"Yu","year":"2015","journal-title":"Remote Sens."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"518","DOI":"10.3390\/f4030518","article-title":"The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning","volume":"4","author":"White","year":"2013","journal-title":"Forests"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.rse.2018.02.002","article-title":"Comparison of airborne laser scanning and digital stereo imagery for characterizing forest canopy gaps in coastal temperate rainforests","volume":"208","author":"White","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_21","doi-asserted-by":"crossref","unstructured":"Tompalski, P., Coops, N., White, J., and Wulder, M. (2016). Enhancing Forest Growth and Yield Predictions with Airborne Laser Scanning Data: Increasing Spatial Detail and Optimizing Yield Curve Selection through Template Matching. Forests, 7.","DOI":"10.3390\/f7110255"},{"key":"ref_22","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_23","doi-asserted-by":"crossref","first-page":"1168","DOI":"10.1016\/j.rse.2007.07.020","article-title":"The uncertainty in conifer plantation growth prediction from multi-temporal lidar datasets","volume":"112","author":"Hopkinson","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_24","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":"Gobakken","year":"2005","journal-title":"Remote Sens. Environ."},{"key":"ref_25","first-page":"1","article-title":"Forest Change Detection by Using Point Clouds From Dense Image Matching Together With a LiDAR-Derived Terrain Model","volume":"10","author":"Packalen","year":"2016","journal-title":"IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"304","DOI":"10.1093\/forestry\/cpu050","article-title":"Assessing height changes in a highly structured forest using regularly acquired aerial image data","volume":"88","author":"Stepper","year":"2014","journal-title":"Forestry"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"1784","DOI":"10.1016\/j.rse.2007.09.002","article-title":"Height growth reconstruction of a boreal forest canopy over a period of 58 years using a combination of photogrammetric and lidar models","volume":"112","year":"2008","journal-title":"Remote Sens. Environ."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"158","DOI":"10.1016\/j.rse.2016.03.012","article-title":"Estimation of forest biomass dynamics in subtropical forests using multi-temporal airborne LiDAR data","volume":"178","author":"Cao","year":"2016","journal-title":"Remote Sens. Environ."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"2938","DOI":"10.1080\/01431161.2016.1219425","article-title":"Updating residual stem volume estimates using ALS- and UAV-acquired stereo-photogrammetric point clouds","volume":"38","author":"Goodbody","year":"2016","journal-title":"Int. J. Remote Sens."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"307","DOI":"10.1016\/j.foreco.2017.09.039","article-title":"Modelling top height growth and site index using repeated laser scanning data","volume":"406","author":"Socha","year":"2017","journal-title":"For. Ecol. Manag."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1139\/X09-183","article-title":"Landscape-scale parametrization of a tree-level forest growth model: A k-nearest neighbor imputation approach incorporating LiDAR data","volume":"40","author":"Falkowski","year":"2010","journal-title":"Can. J. For. Res."},{"key":"ref_32","unstructured":"Dixon, G. (2003). Essential FVS: A User\u2019s Guide to the Forest Vegetation Simulator, Internal Report."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"269","DOI":"10.1080\/07038992.2017.1324288","article-title":"Imputing Tree Lists for New Brunswick Spruce Plantations Through Nearest-Neighbor Matching of Airborne Laser Scan and Inventory Plot Data","volume":"43","author":"Lamb","year":"2017","journal-title":"Can. J. Remote Sens."},{"key":"ref_34","unstructured":"Natural Regions Committee (2006). Natural Regions and Subregions of Alberta, Natural Regions Committee."},{"key":"ref_35","unstructured":"Alberta Sustainable Resource Development (2017, December 04). Alberta Vegetation Inventory Interpretation Standards, Available online: http:\/\/www.srd.gov.ab.ca\/index.html."},{"key":"ref_36","unstructured":"Isenburg, M. (2017, December 01). LAStools. Available online: http:\/\/lastools.org."},{"key":"ref_37","first-page":"110","article-title":"DEM generation from laser scanner data using adaptive TIN models","volume":"33","author":"Axelsson","year":"2000","journal-title":"Int. Arch. Photogramm. Remote Sens."},{"key":"ref_38","unstructured":"McGaughey, R.J. (2017, December 04). FUSION\/LDV: Software for LIDAR Data Analysis and Visualization. Available online: http:\/\/forsys.sefs.uw.edu\/fusion.html."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"322","DOI":"10.1016\/j.rse.2014.10.004","article-title":"Generalizing predictive models of forest inventory attributes using an area-based approach with airborne LiDAR data","volume":"156","author":"Bouvier","year":"2015","journal-title":"Remote Sens. Environ."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"209","DOI":"10.2307\/1937343","article-title":"Correcting for bias in log-transformed allometric equations","volume":"64","author":"Sprugel","year":"1983","journal-title":"Ecology"},{"key":"ref_41","unstructured":"The Forestry Corporation (2018, February 15). Validation Summary of GYPSY Sub-Models, Available online: http:\/\/www1.agric.gov.ab.ca\/$department\/deptdocs.nsf\/all\/formain15784\/$file\/GYPSY-ValidationSummary-SubModelsJun16-2009.pdf?OpenElement."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"692","DOI":"10.1080\/02827581.2012.686625","article-title":"Forest variable estimation using photogrammetric matching of digital aerial images in combination with a high-resolution DEM","volume":"27","author":"Bohlin","year":"2012","journal-title":"Scand. J. For. Res."},{"key":"ref_43","first-page":"685","article-title":"Area-based estimation of growing stock volume in Scots pine stands using ALS and airborne image-based point clouds","volume":"90","author":"Tompalski","year":"2017","journal-title":"Forestry"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"3704","DOI":"10.3390\/f6103704","article-title":"Comparing ALS and Image-Based Point Cloud Metrics and Modelled Forest Inventory Attributes in a Complex Coastal Forest Environment","volume":"6","author":"White","year":"2015","journal-title":"Forests"},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"382","DOI":"10.5589\/m13-046","article-title":"Airborne laser scanning and digital stereo imagery measures of forest structure: Comparative results and implications to forest mapping and inventory update","volume":"39","author":"Vastaranta","year":"2013","journal-title":"Can. J. Remote Sens."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"690","DOI":"10.1139\/cjfr-2016-0439","article-title":"Potential of using data assimilation to support forest planning","volume":"47","author":"Saad","year":"2017","journal-title":"Can. J. For. Res."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"4540","DOI":"10.3390\/f6124384","article-title":"Data assimilation in forest inventory: First empirical results","volume":"6","author":"Lindgren","year":"2015","journal-title":"Forests"},{"key":"ref_48","doi-asserted-by":"crossref","unstructured":"Pascual, A., Pukkala, T., Rodr\u00edguez, F., and de-Miguel, S. (2016). Using spatial optimization to create dynamic harvest blocks from LiDAR-based small interpretation units. Forests, 7.","DOI":"10.3390\/f7100220"}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/2\/347\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:56:09Z","timestamp":1760194569000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/10\/2\/347"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,2,24]]},"references-count":48,"journal-issue":{"issue":"2","published-online":{"date-parts":[[2018,2]]}},"alternative-id":["rs10020347"],"URL":"https:\/\/doi.org\/10.3390\/rs10020347","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2018,2,24]]}}}