Tree species identification in mixed coniferous forest using airborne laser scanning

ISPRS Journal of Photogrammetry and Remote Sensing

Volumn 64, Issue 6, 2009, Pages 683-693

  Suratno, Agus ^a   Seielstad, Carl ^a   Queen, Lloyd ^a  

^a UNIVERSITY OF MONTANA   (United States)

Author keywords

Conifer; Intensity; Laser scanning; North America; Tree species

Indexed keywords

CONIFER; INTENSITY; LASER SCANNING; NORTH AMERICA; TREE SPECIES;

DISCRIMINANT ANALYSIS; LASER APPLICATIONS; LASERS; OPTICAL RADAR; SCANNING;

FORESTRY;

ACCURACY ASSESSMENT; AIRBORNE SENSOR; CANOPY; CONIFEROUS FOREST; DATA INTERPRETATION; DATA SET; DISCRIMINANT ANALYSIS; FOREST CANOPY; LASER; MONTANE FOREST; SCANNER; SPECIES INVENTORY;

BIODIVERSITY; DISCRIMINANT ANALYSIS; FORESTS; LASERS; MAPPING; NORTH AMERICA; REMOTE SENSING; SCANNING; TREES;

NORTH AMERICA;

CONIFEROPHYTA; LARIX OCCIDENTALIS; PINUS CONTORTA; PSEUDOTSUGA; PSEUDOTSUGA MENZIESII;

EID: 70350617798     PISSN: 09242716     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.isprsjprs.2009.07.001     Document Type: Article

References (28)

1. Arno, S.F., Simmerman, D.G., Keane, R.E., 1985. Forest succession on four Habitat types in western Montana. General Technical Report INT-177. USDA Forest Service, Intermountain Forest and Range Experiment Station Ogden, Utah
2. Asner G.P., Lobel D.B., and Law B.E. View angles effects on canopy reflectance and spectral mixture analysis of coniferous forests using AVIRIS. International Journal of Remote Sensing 23 11 (2002) 247-2262
3. Brandtberg T. Classifying individual tree species under leaf-off and leaf-on conditions using airborne lidar. ISPRS Journal of Photogrammetry and Remote Sensing 61 5 (2007) 5-340
4. Clark, R.N., Swayze, G.A., Wise, R., Livo, K.E., Hoefen, T.M., Kokaly, R.F., Sutley, S.J., 2003. USGS Digital Spectral Library splib05a. US Geological Survey. Open File Report 03-395. http://pubs.usgs.gov/of/2003/ofr-03-395/ofr-03-395.html (accessed 12.01.08)
5. Cochrane M.A. Using vegetation reflectance variability for species level classification of hyperspectral data. International Journal of Remote Sensing 21 10 (2000) 2075-2087
6. Donoghue D.N.M., Watt P.J., Cox N.J., and Wilson J. Remote sensing of species mixtures in conifer plantations using LiDAR height and intensity data. Remote Sensing of Environment 110 4 (2007) 509-522
7. Gobakken T., and Naesset E. Estimation of diameter and basal area distributions in coniferous forest by means of airborne laser scanner data. Scandinavian Journal of Forest Research 19 6 (2004) 529-542
8. Holmgren J., and Persson A. Identifying species of individual trees using airborne laser scanning. Remote Sensing of Environment 90 4 (2004) 415-423
9. Korpela I.S. Mapping of understory lichens with airborne discrete-return LiDAR data. Remote Sensing of Environment 112 10 (2008) 3891-3897
10. Laser Technology, 2007. Forest Pro Laser's guide. Centennial, Colorado
11. Leica Geosystems, 2008. ALS50 Airborne Laser Scanner guide. Norcross, Georgia
12. Maas H.G., Bienert A., Scheller S., and Keane E. Automatic forest Inventory parameter determination from terrestrial laser scanner data. International Journal of Remote Sensing 29 5 (2008) 1579-1593
13. Means J.E., Acker S.A., Brandon J.F., Renslow M., Emerson L., and Hendrix C.J. Predicting forest stand characteristics with airborne scanning lidar. Photogrammetric Engineering & Remote Sensing 66 11 (2000) 1367-1371
14. Moffiet T., Mengersen K., Witte C., King R., and Denham R. Airborne laser scanning: Exploratory data analysis indicates potential variables for classification of individual trees of forest stands according to species. ISPRS Journal of Photogrammetry and Remote Sensing 59 5 (2005) 289-309
15. Monserud R.A., and Leemans R. Comparing global vegetation maps with the Kappa statistic. Ecological Modeling 62 4 (1992) 275-293
16. Nimlos, T.J., 1986. Soils of lubrecht experimental forest. Miscellaneous Publication Number 44. Montana Forest and Conservation Experiment Station, Missoula, Montana, 41 p.
17. Oliver C.D., and Larson B.C. Forest Stand Dynamics (1996), Wiley, New York
18. Ørka H.O., Naesset E., and Bollandsas O.M. Utilizing airborne laser intensity for tree species classification. International Archives of Photogrammetry Remote Sensing and Spatial Information Sciences 36 Part 3/W52 (2007) 300-304
19. Persson A., Holmgren J., and Söderman U. Detecting and measuring individual trees using an airborne laser scanner. Photogrammetric Engineering & Remote Sensing 68 9 (2002) 925-932
20. Popescu S.C., and Wynne R.H. Seeing the trees in the forest: Using LIDAR and multispectral data fusion with local filtering and variable window size for estimating tree height. Photogrammetric Engineering & Remote Sensing 70 5 (2004) 589-604
21. Quinn G.P., and Keough M.J. Experimental Design and Data Analysis for Biologists (2002), Cambridge University Press, New York
22. Roth, R., 2007. Personal communication. Leica Geosystems, Inc.
23. Rowell E., Seielstad C., Vierling L., Queen L., and Shepperd W. Using laser Altimetry-base segmentation to refine automated tree identification in managed forests of the Black Hills, South Dakota. Photogrammetric Engineering & Remote Sensing 72 12 (2006) 1379-1388
24. Rowell, E., Seielstad, C., Queen, L., 2009. Implementation and performance of a local-maximum tree stem identification algorithm using vector-format airborne laser scanner data. Manuscript (in preparation)
25. Schreier H., Lougheed J., Tucker C., and Leckie D. Automated measurements of terrain reflection and height variations using an airborne infrared laser system. International Journal of Remote Sensing 6 1 (1985) 101-103
26. Terrasolid, 2004. TerraScan user's guide. Helsinki
27. Warner R.M. Applied Statistics: From Bivariate Through Multivariate Techniques (2008), Sage Publications, California
28. Wheater C.P., and Cook P. Using Statistics to Understand the Environment (2005), Taylor & Francis, New York