{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,19]],"date-time":"2026-02-19T03:01:54Z","timestamp":1771470114616,"version":"3.50.1"},"reference-count":37,"publisher":"MDPI AG","issue":"4","license":[{"start":{"date-parts":[[2022,2,15]],"date-time":"2022-02-15T00:00:00Z","timestamp":1644883200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Hardwood Tree Improvement and Regeneration Center and the USDA Forest Service","award":["19-JV-11242305-102"],"award-info":[{"award-number":["19-JV-11242305-102"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Forest canopy height model (CHM) is useful for analyzing forest stocking and its spatiotemporal variations. However, high-resolution CHM with regional coverage is commonly unavailable due to the high cost of LiDAR data acquisition and computational cost associated with data processing. We present a CHM generation method using U.S. Geological Survey (USGS) 3D Elevation Program (3DEP) LiDAR data for tree height measurement capabilities for entire state of Indiana, USA. The accuracy of height measurement was investigated in relation to LiDAR point density, inventory height, and the timing of data collection. A simple data exploratory analysis (DEA) was conducted to identify problematic input data. Our CHM model has high accuracy compared to field-based height measurement (R2 = 0.85) on plots with relatively accurate GPS locations. Our study provides an easy-to-follow workflow for 3DEP LiDAR based CHM generation in a parallel processing environment for a large geographic area. In addition, the resulting CHM can serve as critical baseline information for monitoring and management decisions, as well as the calculation of other key forest metrics such as biomass and carbon storage.<\/jats:p>","DOI":"10.3390\/rs14040935","type":"journal-article","created":{"date-parts":[[2022,2,15]],"date-time":"2022-02-15T22:44:47Z","timestamp":1644965087000},"page":"935","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":25,"title":["High-Resolution Canopy Height Model Generation and Validation Using USGS 3DEP LiDAR Data in Indiana, USA"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-2337-9693","authenticated-orcid":false,"given":"Sungchan","family":"Oh","sequence":"first","affiliation":[{"name":"Department of Forestry and Natural Resources, Purdue University, 715 West State Street, West Lafayette, IN 47907, USA"},{"name":"Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1176-3540","authenticated-orcid":false,"given":"Jinha","family":"Jung","sequence":"additional","affiliation":[{"name":"Lyles School of Civil Engineering, Purdue University, 550 Stadium Mall Drive, West Lafayette, IN 47907, USA"}]},{"given":"Guofan","family":"Shao","sequence":"additional","affiliation":[{"name":"Department of Forestry and Natural Resources, Purdue University, 715 West State Street, West Lafayette, IN 47907, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3198-966X","authenticated-orcid":false,"given":"Gang","family":"Shao","sequence":"additional","affiliation":[{"name":"Libraries and School of Information Studies, Purdue University, 504 West State Street, West Lafayette, IN 47907, USA"}]},{"given":"Joey","family":"Gallion","sequence":"additional","affiliation":[{"name":"Indiana Department of Natural Resources, 402 West Washington Street, Indianapolis, IN 46204, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2772-0166","authenticated-orcid":false,"given":"Songlin","family":"Fei","sequence":"additional","affiliation":[{"name":"Department of Forestry and Natural Resources, Purdue University, 715 West State Street, West Lafayette, IN 47907, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,2,15]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1139\/X08-205","article-title":"Accuracy and Equivalence Testing of Crown Ratio Models and Assessment of Their Impact on Diameter Growth and Basal Area Increment Predictions of Two Variants of the Forest Vegetation Simulator","volume":"39","author":"Leites","year":"2009","journal-title":"Can. J. For. Res."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1038\/s41561-018-0147-z","article-title":"Tree Height Matters","volume":"11","author":"Brando","year":"2018","journal-title":"Nat. Geosci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"1284","DOI":"10.1016\/j.jenvman.2018.09.100","article-title":"Factors Influencing the Accuracy of Ground-Based Tree-Height Measurements for Major European Tree Species","volume":"231","author":"Mielcarek","year":"2019","journal-title":"J. Environ. Manag."},{"key":"ref_4","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_5","doi-asserted-by":"crossref","first-page":"225","DOI":"10.7809\/b-e.00079","article-title":"Forest Inventory and Analysis Database of the United States of America (FIA)","volume":"4","author":"Gray","year":"2012","journal-title":"Biodivers. Ecol."},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1519","DOI":"10.3390\/rs4061519","article-title":"Development of a UAV-LiDAR System with Application to Forest Inventory","volume":"4","author":"Wallace","year":"2012","journal-title":"Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"114011","DOI":"10.1088\/1748-9326\/ab49bb","article-title":"Structural Diversity as a Predictor of Ecosystem Function","volume":"14","author":"Larue","year":"2019","journal-title":"Environ. Res. Lett."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"872","DOI":"10.1016\/j.rse.2017.09.011","article-title":"Improving Lidar-Based Aboveground Biomass Estimation of Temperate Hardwood Forests with Varying Site Productivity","volume":"204","author":"Shao","year":"2018","journal-title":"Remote Sens. Environ."},{"key":"ref_9","first-page":"105","article-title":"Influence of Micro-Topography and Crown Characteristics on Tree Height Estimations in Tropical Forests Based on LiDAR Canopy Height Models","volume":"65","author":"Alexander","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"355","DOI":"10.5589\/m06-030","article-title":"A Rigorous Assessment of Tree Height Measurements Obtained Using Airborne Lidar and Conventional Field Methods","volume":"32","author":"Andersen","year":"2006","journal-title":"Can. J. Remote Sens."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Barnes, C., Balzter, H., Barrett, K., Eddy, J., Milner, S., and Su\u00e1rez, J.C. (2017). Remote Sensing Individual Tree Crown Delineation from Airborne Laser Scanning for Diseased Larch Forest Stands. Remote Sens., 9.","DOI":"10.3390\/rs9030231"},{"key":"ref_12","first-page":"145","article-title":"Modeling Mediterranean Forest Structure Using Airborne Laser Scanning Data","volume":"57","author":"Bottalico","year":"2017","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"7671","DOI":"10.1080\/01431161.2013.823523","article-title":"A Mixed Pixel-and Region-Based Approach for Using Airborne Laser Scanning Data for Individual Tree Crown Delineation in Pinus Radiata D. Don Plantations","volume":"34","author":"Barbosa","year":"2013","journal-title":"Int. J. Remote Sens."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"108736","DOI":"10.1016\/j.ecolmodel.2019.108736","article-title":"Optimizing Individual Tree Detection Accuracy and Measuring Forest Uniformity in Coconut (Cocos Nucifera L.) Plantations Using Airborne Laser Scanning","volume":"409","author":"Mohan","year":"2019","journal-title":"Ecol. Model."},{"key":"ref_15","first-page":"132","article-title":"Testing and Evaluating Different LiDAR-Derived Canopy Height Model Generation Methods for Tree Height Estimation","volume":"71","author":"Mielcarek","year":"2018","journal-title":"Int. J. Appl. Earth Obs. Geoinf."},{"key":"ref_16","doi-asserted-by":"crossref","unstructured":"Sibona, E., Vitali, A., Meloni, F., Caffo, L., Dotta, A., Lingua, E., Motta, R., and Garbarino, M. (2017). Direct Measurement of Tree Height Provides Different Results on the Assessment of LiDAR Accuracy. Forests, 8.","DOI":"10.3390\/f8010007"},{"key":"ref_17","first-page":"139","article-title":"Challenges to Estimating Tree Height via LiDAR in Closed-Canopy Forests: A Parable from Western Oregon","volume":"56","author":"Gatziolis","year":"2010","journal-title":"For. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"425","DOI":"10.1007\/s10310-007-0041-9","article-title":"Detection of Individual Trees and Estimation of Tree Height Using LiDAR Data","volume":"12","author":"Kwak","year":"2007","journal-title":"J. For. Res."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1567","DOI":"10.14214\/sf.1567","article-title":"Nationwide Airborne Laser Scanning Based Models for Volume, Biomass and Dominant Height in Finland","volume":"50","author":"Kotivuori","year":"2016","journal-title":"Silva Fenn."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"555","DOI":"10.1080\/01431161.2018.1516311","article-title":"Comparison of a Commercial and Home-Assembled Fixed-Wing UAV for Terrain Mapping of a Post-Mining Site under Leaf-off Conditions","volume":"40","author":"Urban","year":"2019","journal-title":"Int. J. Remote Sens."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"447","DOI":"10.1016\/j.rse.2016.10.022","article-title":"A Nationwide Forest Attribute Map of Sweden Predicted Using Airborne Laser Scanning Data and Field Data from the National Forest Inventory","volume":"194","author":"Nilsson","year":"2017","journal-title":"Remote Sens. Environ."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Karl Heidemann, H. (2012). National Geospatial Program Lidar Base Specification Lidar Base Specification Techniques and Methods 11-B4.","DOI":"10.3133\/tm11B4"},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"095003","DOI":"10.1088\/1748-9326\/ab93f9","article-title":"A Carbon Monitoring System for Mapping Regional, Annual Aboveground Biomass across the Northwestern USA","volume":"15","author":"Hudak","year":"2020","journal-title":"Environ. Res. Lett."},{"key":"ref_24","doi-asserted-by":"crossref","unstructured":"Obata, S., Cieszewski, C.J., Lowe, R.C., and Bettinger, P. (2021). Random Forest Regression Model for Estimation of the Growing Stock Volumes in Georgia, Usa, Using Dense Landsat Time Series and Fia Dataset. Remote Sens., 13.","DOI":"10.3390\/rs13020218"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"1483","DOI":"10.23953\/cloud.ijarsg.40","article-title":"Evaluating Lidar Point Densities for Effective Estimation of Aboveground Biomass","volume":"5","author":"Vogel","year":"2016","journal-title":"Int. J. Adv. Remote Sens. GIS"},{"key":"ref_26","unstructured":"Parker, R.C., Glass, P.A., Londo, H.A., Evans, D.L., Belli, K.L., Matney, T.G., and Schultz, E.B. (2007). Use of Computer and Spatial Technologies in Large Area Inventories, Forest and Wildlife Research Center, Mississippi State University."},{"key":"ref_27","unstructured":"(2021, December 27). Guidelines for Digital Elevation Data. Available online: https:\/\/giscenter.isu.edu\/pdf\/NDEPElevationGuidelinesVer1.pdf."},{"key":"ref_28","unstructured":"(2021, August 04). IGIC Indiana\u2019s New 3DEP LiDAR Data and Informational Resources. Available online: https:\/\/igic.memberclicks.net\/indiana-s-new-3dep-lidar-data-and-informational-resources."},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"184","DOI":"10.1016\/j.isprsjprs.2020.02.019","article-title":"Conterminous United States Land Cover Change Patterns 2001\u20132016 from the 2016 National Land Cover Database","volume":"162","author":"Homer","year":"2020","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_30","unstructured":"Jung, J., and Oh, S. (2021, December 27). Indiana Statewide Normalized Digital Height Model (2016\u20132019). Available online: Lidar.jinha.org."},{"key":"ref_31","unstructured":"Jung, J., and Oh, S. (2021, December 27). LiDAR Data Hosted by IDiF. Available online: Lidar.digitalforestry.org."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"118284","DOI":"10.1016\/j.foreco.2020.118284","article-title":"Modeling Realized Gains in Douglas-Fir (Pseudotsuga Menziesii) Using Laser Scanning Data from Unmanned Aircraft Systems (UAS)","volume":"473","author":"Grubinger","year":"2020","journal-title":"For. Ecol. Manag."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"1339","DOI":"10.1080\/01431160701736489","article-title":"Methods of Small-Footprint Airborne Laser Scanning for Extracting Forest Inventory Data in Boreal Forests","volume":"29","author":"Leckie","year":"2008","journal-title":"Int. J. Remote Sens."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"1071","DOI":"10.14358\/PERS.71.9.1071","article-title":"Effects of Forest Environment and Survey Protocol on GPS Accuracy","volume":"71","author":"Piedallu","year":"2005","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"3595","DOI":"10.1080\/014311699211228","article-title":"Impact of Forest Canopy on Quality and Accuracy of GPS Measurements","volume":"20","author":"Sigrist","year":"1999","journal-title":"Int. J. Remote Sens."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"539","DOI":"10.1007\/978-81-322-2728-1_50","article-title":"An Adaptive Filter Approach for GPS Multipath Error Estimation and Mitigation","volume":"Volume 372","author":"Swathi","year":"2016","journal-title":"Lecture Notes in Electrical Engineering"},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"863","DOI":"10.14358\/PERS.80.9.863","article-title":"Generating Pit-Free Canopy Height Models from Airborne Lidar","volume":"80","author":"Khosravipour","year":"2014","journal-title":"Photogramm. Eng. Remote Sens."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/4\/935\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T22:19:57Z","timestamp":1760134797000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/14\/4\/935"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,2,15]]},"references-count":37,"journal-issue":{"issue":"4","published-online":{"date-parts":[[2022,2]]}},"alternative-id":["rs14040935"],"URL":"https:\/\/doi.org\/10.3390\/rs14040935","relation":{},"ISSN":["2072-4292"],"issn-type":[{"value":"2072-4292","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,2,15]]}}}