Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State
The monitoring and assessment of forest conditions has traditionally relied on continuous forest inventory (CFI) plots, where all plot trees are regularly measured at discrete locations, then plots are grouped as representative samples of forested areas via stand-based inventory expectations. Remote...
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MDPI AG
2025-05-01
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| author | Thomas Montzka Steve Scharosch Michael Huebschmann Mark V. Corrao Douglas D. Hardman Scott W. Rainsford Alistair M. S. Smith The Confederated Tribes and Bands of the Yakama Nation |
| author_facet | Thomas Montzka Steve Scharosch Michael Huebschmann Mark V. Corrao Douglas D. Hardman Scott W. Rainsford Alistair M. S. Smith The Confederated Tribes and Bands of the Yakama Nation |
| author_sort | Thomas Montzka |
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| description | The monitoring and assessment of forest conditions has traditionally relied on continuous forest inventory (CFI) plots, where all plot trees are regularly measured at discrete locations, then plots are grouped as representative samples of forested areas via stand-based inventory expectations. Remote sensing data acquisitions, such as airborne laser scanning (ALS), are becoming more widely applied to operational forestry to derive similar stand-based inventories. Although ALS systems are widely applied to assess forest metrics associated with crowns and canopies, limited studies have compared ALS-derived digital inventories to CFI datasets. In this study, we conducted an analysis of over 1000 CFI plot locations on ~611,000 acres and compared it to a single-tree derived inventory. Inventory metrics from CFI data were forward modeled from 2016 to 2019 using the USDA Forest Service Forest Vegetation Simulator (FVS) to produce estimates of trees per acre (TPA), basal area (BA) per tree or per plot, basal area per acre (BAA), and volume per acre (VPA) and compared to the ALS-derived Digital Inventory<sup>®</sup> (DI) of 2019. The CFI data provided greater on-plot tree counts, BA, and volume compared to the DI when limited to trees ≥5 inches DBH. On-plot differences were less significant for taller trees and increasingly diverged for shorter trees (<20 feet tall) known to be less detectable by ALS. The CFI volume was found to be 44% higher than the ALS-derived DI suggesting mean volume per acre as derived from plot sampling methods may not provide accurate results when expanded across the landscape given variable forest conditions not captured during sampling. These results provide support that when used together, CFI and DI datasets represent a powerful set of tools within the forest management toolkit. |
| format | Article |
| id | doaj-art-74d7ca896dda4398a2e52421115d3ea8 |
| institution | Kabale University |
| issn | 2072-4292 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj-art-74d7ca896dda4398a2e52421115d3ea82025-08-20T03:47:58ZengMDPI AGRemote Sensing2072-42922025-05-011710176110.3390/rs17101761Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington StateThomas Montzka0Steve Scharosch1Michael Huebschmann2Mark V. Corrao3Douglas D. Hardman4Scott W. Rainsford5Alistair M. S. Smith6The Confederated Tribes and Bands of the Yakama Nation7Delphi Advisors, Boise, ID 83702, USADelphi Advisors, Boise, ID 83702, USADelphi Advisors, Boise, ID 83702, USANorthwest Management Inc., Moscow, ID 83843, USADepartment of Forest, Rangeland, and Fire Sciences, College of Natural Resources, University of Idaho, Moscow, ID 83844, USADepartment of Earth and Spatial Sciences, College of Science, University of Idaho, Moscow, ID 83844, USADepartment of Earth and Spatial Sciences, College of Science, University of Idaho, Moscow, ID 83844, USAMain Agency Offices, 401 Fort Road, Toppenish, WA 98948, USAThe monitoring and assessment of forest conditions has traditionally relied on continuous forest inventory (CFI) plots, where all plot trees are regularly measured at discrete locations, then plots are grouped as representative samples of forested areas via stand-based inventory expectations. Remote sensing data acquisitions, such as airborne laser scanning (ALS), are becoming more widely applied to operational forestry to derive similar stand-based inventories. Although ALS systems are widely applied to assess forest metrics associated with crowns and canopies, limited studies have compared ALS-derived digital inventories to CFI datasets. In this study, we conducted an analysis of over 1000 CFI plot locations on ~611,000 acres and compared it to a single-tree derived inventory. Inventory metrics from CFI data were forward modeled from 2016 to 2019 using the USDA Forest Service Forest Vegetation Simulator (FVS) to produce estimates of trees per acre (TPA), basal area (BA) per tree or per plot, basal area per acre (BAA), and volume per acre (VPA) and compared to the ALS-derived Digital Inventory<sup>®</sup> (DI) of 2019. The CFI data provided greater on-plot tree counts, BA, and volume compared to the DI when limited to trees ≥5 inches DBH. On-plot differences were less significant for taller trees and increasingly diverged for shorter trees (<20 feet tall) known to be less detectable by ALS. The CFI volume was found to be 44% higher than the ALS-derived DI suggesting mean volume per acre as derived from plot sampling methods may not provide accurate results when expanded across the landscape given variable forest conditions not captured during sampling. These results provide support that when used together, CFI and DI datasets represent a powerful set of tools within the forest management toolkit.https://www.mdpi.com/2072-4292/17/10/1761forestryLiDARcontinuous forest inventory |
| spellingShingle | Thomas Montzka Steve Scharosch Michael Huebschmann Mark V. Corrao Douglas D. Hardman Scott W. Rainsford Alistair M. S. Smith The Confederated Tribes and Bands of the Yakama Nation Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State Remote Sensing forestry LiDAR continuous forest inventory |
| title | Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State |
| title_full | Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State |
| title_fullStr | Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State |
| title_full_unstemmed | Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State |
| title_short | Comparison of a Continuous Forest Inventory to an ALS-Derived Digital Inventory in Washington State |
| title_sort | comparison of a continuous forest inventory to an als derived digital inventory in washington state |
| topic | forestry LiDAR continuous forest inventory |
| url | https://www.mdpi.com/2072-4292/17/10/1761 |
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