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RESEARCH ARTICLE
Contents Vol 19(1)

Applying LiDAR technology for tree measurements in burned landscapes

Michael G. Wing A B , Aaron Eklund A and John Sessions A
+ Author Affiliations
- Author Affiliations

A Peavy Hall 204, Forest Engineering, Resources, and Management, Oregon State University, Corvallis, OR 97331, USA.

B Corresponding author. Email: michael.wing@oregonstate.edu

International Journal of Wildland Fire 19(1) 104-114 https://doi.org/10.1071/WF08170
Submitted: 3 October 2008  Accepted: 22 June 2009   Published: 5 February 2010

Abstract

Wildfires burn several million hectares in the United States annually. Time is critical in gathering information from burned landscapes for post-fire recovery planning. A technology to obtain spatial vegetation information across landscapes is Light Detecting and Ranging (LiDAR). We compared tree positional and height measurements, primarily from Douglas-fir (Pseudotsuga menziesii) and ponderosa pine (Pinus ponderosa), between field-based and LiDAR-derived measurements at three south-western Oregon (USA) sites. The sites represented a range of tree mortality from minimal to extensive. Our primary objective was to determine whether significant differences existed between field and LiDAR tree measurements in burned landscapes. Secondary objectives were to examine whether LiDAR pulse intensities in burned landscapes could differentiate coniferous from deciduous trees, discern fire-killed from live trees, and whether other tree measurement parameters were related to pulse intensities. No significant differences were detected between field-based and LiDAR-derived horizontal positions. Tree height differences between field-based and LiDAR measurements were significant at one site likely owing to dense canopy and measurement biases. Mean and maximum LiDAR intensities were significantly different between live and dead (fire-killed) trees in two of three sites. Additionally, crown diameter and tree sweep were significant in explaining variation in maximum LiDAR intensities at all sites.

Additional keywords: geospatial, GPS, wildfire.


Acknowledgements

We gratefully acknowledge the University of Washington Precision Forestry Cooperative for providing LiDAR data and assistance with this study.


References


Andersen H-E, Reutebuch SE , McGaughey RJ (2006) A rigorous assessment of tree height measurements obtained using airborne LiDAR and conventional field methods. Canadian Journal of Remote Sensing  32(5), 355–366.
Bormann BT, Kerns BK, Evans J, Nay M, Hudak A, Darbyshire R, Kiester R (2006) FCSSF Project C4 – using remote sensing to evaluate biodiversity indicators: implications for Biscuit post-fire restoration. Final Report to the National Commission on Science for Sustainable Forestry, Pacific Northwest Research Station, 15 March 2006. (Corvallis, OR)

Brandtberg T, Warner TA, Landenberger RE , McGraw JB (2003) Detection and analysis of individual leaf-off tree crowns in small-footprint, high sampling density lidar data from the eastern deciduous forest in North America. Remote Sensing of Environment  85, 290–303.
| Crossref | GoogleScholarGoogle Scholar | Dorren L, Maier B, Berger F (2006) Assessing protection forest structure with airborne laser scanning in steep mountainous terrain. In ‘Proceedings from Workshop on 3D Remote Sensing in Forestry’, 14–15 February 2006, Vienna, Austria. (Eds T Koukal, W Schneider) pp. 238–242. (European Association of Remote Sensing Laboratories: Vienna)

Eklund A, Wing MG , Sessions J (2009) Evaluating economic and wildlife habitat considerations for snag retention policies in burned landscapes. Western Journal of Applied Forestry  24(2), 67–75.
Hyyppä J, Pyysalo U, Hyyppä H, Samberg A (2000) Elevation accuracy of laser scanning-derived digital terrain and target models in forest environment. In ‘Proceedings of EARSeL–SIG Workshop LIDAR’, 16–17 June 2000, Dresden, Germany. EARSeL eProceedings No. 1, pp. 139–147. (European Association of Remote Sensing Laboratories) Available at http://las.physik.uni-oldenburg.de/eProceedings/vol01_1/01_1_hyyppae1.pdf [Verified 23 January 2010]

Imai Y, Setojima M, Yamagishi Y, Fujiwara N (2004) Tree-height measuring characteristics of urban forests by LiDAR data different in resolution. In ‘International Society of Photogrammetry and Remote Sensing 2004 Conference Proceedings’, 12–23 July 2004, Istanbul, Turkey. Commission VII. pp. 513–517.(International Society for Photogrammetry and Remote Sensing: Istanbul, Turkey)

Lefsky MA, Cohen WB, Parker GG , Harding DJ (2002) Lidar remote sensing for ecosystem studies. Bioscience  52(1), 19–30.
| Crossref | GoogleScholarGoogle Scholar | Lim K, Treitz P, Groot A, St-Onge B (2001) Estimation of individual tree heights using LiDAR remote sensing. In ‘Proceedings of the 23rd Annual Canadian Symposium on Remote Sensing’, 20–24 August 2001, Quebec, QC. pp. 243–250. (Canadian Aeronautics and Space Institute: Ottawa, ON)

Maltamo M, Mustonen K, Hyyppä J, Pitkänen J , Yu X (2004) The accuracy of estimating individual tree variables with airborne laser scanning in a boreal nature reserve. Canadian Journal of Forest Research  34, 1791–1801.
| Crossref | GoogleScholarGoogle Scholar | Reinhardt E, Crookston NL (Eds) (2003) The Fire and Fuels Extension to the Forest Vegetation Simulator. USDA Forest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-116. (Ogden, UT)

Remote Sensing Applications Center (RSAC) (2008) Introduction to Fusion. Available at http://www.fs.fed.us/eng/rsac/fusion/ [Verified 18 September 2008]

Renslow M, Greenfield P, Guay T (2000) Evaluation of multi-return LIDAR for forestry applications. USDA Forest Service – Engineering, Remote Sensing Applications Center RSAC-2060/4180-LSP-0001–RPT1. (Salt Lake City, UT)

Reutebuch SE, McGaughey RJ, Andersen H-E , Carson WW (2003) Accuracy of a high-resolution lidar terrain model under a conifer forest canopy. Canadian Journal of Remote Sensing  29(5), 527–535.
Samberg A, Hyyppä J (1999) Assessing tree attributes from the laser scanner data: the high-scan case. In ‘Proceedings of the Fourth International Airborne Remote Sensing Conference and Exhibition’, 21–24 June 1999, Ottawa, ON. pp. 251–258.

Song J-H, Han S-H, Yu K, Kim Y-I (2002) Assessing the possibility of land-cover classification using lidar intensity data. In ‘International Society of Photogrammetry and Remote Sensing (ISPRS) Commission III Symposium 2002’, 9–13 September 2002, Graz, Austria. Vol. XXXIV, pp. B-259–262. (ISPRS: Amsterdam, the Netherlands)

Wing MG, Solmie D , Kellogg L (2004) Comparing digital range finders for forestry applications. Journal of Forestry  102(4), 16–20.


Wing MG, Eklund A, Sessions J , Karsky R (2008) Horizontal measurement performance of five mapping-grade GPS receiver configurations in several forested settings. Western Journal of Applied Forestry  23(3), 166–171.


Yu X, Hyyppä J, Kukko A, Maltamo M , Kaartinen H (2006) Change detection techniques for canopy height growth measurements using airborne laser scanner data. Photogrammetric Engineering and Remote Sensing  72(12), 1339–1348.