{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,12]],"date-time":"2026-02-12T16:59:00Z","timestamp":1770915540990,"version":"3.50.1"},"reference-count":66,"publisher":"MDPI AG","issue":"11","license":[{"start":{"date-parts":[[2022,5,27]],"date-time":"2022-05-27T00:00:00Z","timestamp":1653609600000},"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>Globally, remotely sensed data and, in particular, Airborne Laser Scanning (ALS), are being assessed by the forestry industry for their ability to acquire accurate forest inventories at an individual-tree level. This pilot study compares an inventory derived using the ForestView\u00ae biometrics analysis system to traditional cruise measurements and felled tree measurements for 139 Pinus taeda sp. (loblolly pine) trees in eastern Texas. The Individual Tree Detection (ITD) accuracy of ForestView\u00ae was 97.1%. In terms of tree height accuracy, ForestView\u00ae results had an overall lower mean bias and RMSE than the traditional cruise techniques when both datasets were compared to the felled tree data (LiDAR: mean bias = 1.1 cm, RMSE = 41.2 cm; Cruise: mean bias = 13.8 cm, RMSE = 57.5 cm). No significant difference in mean tree height was observed between the felled tree, cruise, and LiDAR measurements (p-value = 0.58). ForestView-derived DBH exhibited a \u22122.1 cm bias compared to felled-tree measurements. This study demonstrates the utility of this newly emerging ITD software as an approach to characterize forest structure on similar coniferous forests landscapes.<\/jats:p>","DOI":"10.3390\/rs14112567","type":"journal-article","created":{"date-parts":[[2022,5,31]],"date-time":"2022-05-31T00:25:12Z","timestamp":1653956712000},"page":"2567","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":14,"title":["A Conventional Cruise and Felled-Tree Validation of Individual Tree Diameter, Height and Volume Derived from Airborne Laser Scanning Data of a Loblolly Pine (P. taeda) Stand in Eastern Texas"],"prefix":"10.3390","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-0400-0716","authenticated-orcid":false,"given":"Mark V.","family":"Corrao","sequence":"first","affiliation":[{"name":"Department of Forest, Rangeland, and Fire Sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1286-3770","authenticated-orcid":false,"given":"Aaron M.","family":"Sparks","sequence":"additional","affiliation":[{"name":"Department of Forest, Rangeland, and Fire Sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USA"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0071-9958","authenticated-orcid":false,"given":"Alistair M. S.","family":"Smith","sequence":"additional","affiliation":[{"name":"Department of Forest, Rangeland, and Fire Sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USA"},{"name":"Department of Department of Earth and Spatial Sciences, College of Science, University of Idaho, Moscow, ID 83844, USA"}]}],"member":"1968","published-online":{"date-parts":[[2022,5,27]]},"reference":[{"key":"ref_1","first-page":"191","article-title":"Predicting Forest Stand Variables from Airborne LiDAR Data Using a Tree Detection Method in Central European Forests","volume":"66","author":"Scheer","year":"2019","journal-title":"Cent. Eur. For. J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Sparks, A.M., and Smith, A.M.S. (2022). Accuracy of a LiDAR-Based Individual Tree Detection and Attribute Measurement Algorithm Developed to Inform Forest Products Supply Chain and Resource Management. 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