Estimation of forest structure and canopy fuel parameters from small-footprint full-waveform LiDAR data

International Journal of Wildland Fire

Volumn 23, Issue 2, 2014, Pages 224-233

  Hermosilla, Txomin ^a,b   Ruiz, Luis A ^a   Kazakova, Alexandra N ^c   Coops, Nicholas C ^b   Moskal, L Monika ^c  

^a UNIVERSITAT POLITÈCNICA DE VALÈNCIA   (Spain)

^b UNIVERSITY OF BRITISH COLUMBIA   (Canada)

^c University of Washington   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 84896944660     PISSN: 10498001     EISSN: None     Source Type: Journal    
DOI: 10.1071/WF13086     Document Type: Article

References (63)

1. Agee J (1996) 'Fire Ecology of Pacific Northwest Forests.' (Island Press: Washington, DC)
2. Ahokas E, Kaasalainen S, Hyyppä J, Suomalainen J (2006) Calibration of the Optech ALTM3100 laser scanner intensity data using brightness targets. In 'ISPRS Archives - Volume XXXVI Part 1, 2006, ISPRS Commission I Symposium: From Sensors to Imagery', 4-6 May 2006, Paris. (Eds A Baudoin, N Paparoditis) (Copernicus Publications for the International Society of Photogrammetry and Remote Sensing) Available at http://www.isprs.org/proceedings/XXXVI/part1/ Papers/T03-11.pdf [Verified 23 October 2013]
3. Akaike H (1974) A new look at the statistical model identification. IEEE Transactions on Automatic Control 19, 716-723.
4. Anderson HE (1982) Aids to determining fuel models for estimating fire behavior. USDA Forest Service, Intermountain Forest and Range Experiment Station, General Technical Report INT-122. (Ogden, UT)
5. Andersen HE, McGaughey RJ, Reutebuch SE (2005) Estimating forest canopy fuel parameters using LiDAR data. Remote Sensing of Environment 94, 441-449. doi:10.1016/J.RSE.2004.10.013
6. Andrews PL (2009) Behave Plus fire modeling system, version 5.0: Variables. USDAForest Service, Rocky Mountain Research Station, General Technical Report RMRS-GTR-213WWW Revised. (Fort Collins, CO)
7. Arroyo LA, Pascual C, Manzanera JA (2008) Fire models and methods to map fuel types: the role of remote sensing. Forest Ecology and Management 256, 1239-1252. doi:10.1016/J.FORECO.2008.06.048
8. Ashworth A, Evans DL, Cooke WH, Londo A, Collins C, Neuenschwander A (2010) Predicting southeastern forest canopy heights and fire fuel models using GLAS data. Photogrammetric Engineering and Remote Sensing 76, 915-922.
9. Bailey RG (1995) Description of the ecoregions of the United States, 2nd edn. USDA Forest Service, Miscellaneous Publication 1391. (Washington, DC)
10. Buddenbaum H, Seeling S, Hill J (2013) Fusion of full-waveform LiDAR and imaging spectroscopy remote sensing data for the characterization of forest stands. International Journal of Remote Sensing 34, 4511-4524. doi:10.1080/01431161.2013.776721
11. Chuvieco E, Congalton RG (1989) Application of remote sensing and geographic information systems to forest fire hazard mapping. Remote Sensing of Environment 29, 147-159. doi:10.1016/0034-4257(89) 90023-0
12. Chuvieco E, Salas J (1996) Mapping the spatial distribution of forest fire danger using GIS. International Journal of Geographical Information Science 10, 333-345.
13. Chuvieco E, Riano D, Aguado I, Cocero D (2002) Estimation of fuel moisture content from multitemporal analysis of Landsat Thematic Mapper reflectance data: applications in fire danger assessment. International Journal of Remote Sensing 23, 2145-2162. doi:10.1080/01431160110069818
14. Chuvieco E, Riano D, Van Wagtendok J, Morsdof F (2003) Fuel loads and fuel type mapping, in wildland fire danger estimation and mapping: the role of remote sensing data. World Scientific 4, 119-142.
15. Chuvieco E, Cocero D, Riano D, Martin P, Marti{dotless}nez-Vega J, de la Riva J, Pérez F (2004) Combining NDVI and surface temperature for the estimation of live fuel moisture content in forest fire danger rating. Remote Sensing of Environment 92, 322-331. doi:10.1016/J.RSE.2004. 01.019
16. Cruz MG, Alexander ME, Wakimoto RH (2003) Assessing canopy fuel stratum characteristics in crown fire prone fuel types of western North America. International Journal of Wildland Fire 12, 39-50. doi:10.1071/WF02024
17. Drake JB, Dubayah RO, Clark DB, Knox RG, Blair JB, Hofton MA, Chazdon RL, Weishampel JF, Prince S (2002) Estimation of tropical forest structural characteristics using large-footprint LiDAR. Remote Sensing of Environment 79, 305-319. doi:10.1016/S0034-4257(01) 00281-4
18. Duong HV (2010) Processing and application of ICESat large footprint full waveform laser range data. PhD Thesis, Delft University of Technology.
19. Erdody TL, Moskal LM (2010) Fusion of LiDAR and imagery for estimating forest canopy fuels. Remote Sensing of Environment 114, 725-737. doi:10.1016/J.RSE.2009.11.002
20. Falkowski MJ, Gessler PE, Morgan P, Hudak AT, Smith A (2005) Characterizing and mapping forest fire fuels using ASTER imagery and gradient modeling. Forest Ecology and Management 217, 129-146. doi:10.1016/J.FORECO.2005. 06.013
21. Finney MA (2004) FARSITE: fire area simulator-model development and evaluation. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-4, revised edition. (Ogden, UT)
22. Flannigan MD, Stocks BJ, Wotton BM (2000) Climate change and forest fires. The Science of the Total Environment 262, 221-229. doi:10.1016/S0048- 9697(00)00524-6
23. Flewelling JW, McFadden G(2011) LiDAR data and cooperative research at Panther Creek, Oregon. In 'Proceedings of Silvi Laser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems', 16-20 October 2011, Hobart, Tas., Australia. (Ed. J Rombouts) (Conference Design Pty Ltd: Hobart) Available at http://www.iufro.org/download/file/8240/1742/40205- silvilaser2011- pdf/ [Verified 23 October 2013]
24. García M, Popescu S, Riaño D, Zhao K, Neuenschwander A, Agca M, Chuvieco E (2012) Characterization of canopy fuels using ICESat/GLAS data. Remote Sensing of Environment 123, 81-89. doi:10.1016/J.RSE.2012.03.018
25. Gholz HL (1979) Equations for estimating biomass and leaf area of plants in the Pacific Northwest. Oregon State University, Forest Research Laboratory, (Corvallis OR)
26. González-Olabarria JR, Rodríguez F, Fernández-Landa A, Mola-Yudego B (2012) Mapping fire risk in the Model Forest of Urbión (Spain) based on airborne LiDAR measurements. Forest Ecology and Management 282, 149-156. doi:10.1016/J.FORECO.2012.06.056
27. Guang Cai X, Yong P, Zengyuana L, Dan Z, Luxia L (2012) Individual trees species classification using relative calibrated full-waveform LiDAR data. In 'Silvi Laser 2012: 12th International Conference on LiDAR Applications for Assessing Forest Ecosystems', 16-19 September 2012, Vancouver, BC. (Eds NCC Coops, MA Wulder) Paper SL2012-084. (Vancouver, BC) Available at http://silvilaser2012.com/wp-content/uploads/2011/11/Silvilaser2012-Full- Proceedings.pdf [Verified 23 October 2013]
28. Hall SA, Burke IC, Box DO, Kaufmann MR, Stoker JM (2005) Estimating stand structure using discrete-return LiDAR: an example from low density, fire prone ponderosa pine forests. Forest Ecology and Management 208, 189-209. doi:10.1016/J.FORECO.2004.12.001
29. Harding DJ, Carabajal CC (2005) ICESat waveform measurements of within-footprint topographic relief and vegetation vertical structure. Geophysical Research Letters 32, L21S10. doi:10.1029/2005GL023471
30. Heinzel J, Koch B (2011) Exploring full-waveform LiDAR parameters for tree species classification. International Journal of Applied Earth Observation and Geoinformation 13, 152-160. doi:10.1016/J.JAG.2010.09.010
31. Hippenstiel R, Brownson JR (2012) Computing solar energy potential of urban areas using airborne LiDAR and orthoimagery. In 'Proceedings of the National Solar Conference and World Renewable Energy Forum 3, 2004-2008'. 13-17 May 2012, Denver, CO. (Boulder, CO) Available at http://ases.conference- services.net/resources/252/2859/pdf/SOLAR2012-0296-full%20paper.pdf [Verified 23 October 2013]
32. Höfle B, Hollaus M, Hagenauer J (2012) Urban vegetation detection using radiometrically calibrated small-footprint full-waveform airborne LiDAR data. ISPRS Journal of Photogrammetry and Remote Sensing 67, 134-147. doi:10.1016/J.ISPRSJPRS.2011.12.003
33. Hyde P, Dubayah R, Peterson B, Blair JB, Hofton M, Hunsaker C, Walker W (2005) Mapping forest structure for wildlife habitat analysis using waveform LiDAR: validation of montane ecosystems. Remote Sensing of Environment 96, 427-437. doi:10.1016/J.RSE. 2005.03.005
34. Keane RE, Burgan R, Van Wagtendonk J (2001) Mapping wildland fuels for fire management across multiple scales: integrating remote sensing, GIS, and biophysical modeling. International Journal of Wildland Fire 10, 301-319. doi:10.1071/WF01028
35. Kim Y, Yang Z, Cohen WB, Pflugmacher D, Lauver CL, Vankat JL (2009) Distinguishing between live and dead standing tree biomass on the North Rim of Grand Canyon National Park, USA small-footprint LiDAR data. Remote Sensing of Environment 113, 2499-2510. doi:10.1016/J.RSE.2009.07.010
36. Koetz B, Morsdorf F, Sun G, Ranson KJ, Itten K, Allgower B (2006) Inversion of a LiDAR waveform model for forest biophysical parameter estimation. Geoscience and Remote Sensing Letters, IEEE 3, 49-53. doi:10.1109/LGRS.2005. 856706
37. Lefsky MA, Cohen WB, Acker SA, Parker GG, Spies TA, Harding D (1999) LiDAR remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests. Remote Sensing of Environment 70, 339-361. doi:10.1016/S0034-4257(99)00052-8
38. Listopad CM, Drake JB, Masters RE, Weishampel JF (2011) Portable and airborne small footprint LiDAR: forest canopy structure estimation of fire managed plots. Remote Sensing 3, 1284-1307. doi:10.3390/RS3071284
39. Mallet C, Bretar F (2009) Full-waveform topographic LiDAR: state-of-theart. ISPRS Journal of Photogrammetry and Remote Sensing 64, 1-16. doi:10.1016/J.ISPRSJPRS.2008.09.007
40. Mooney HA, Bonnicksen TM, Christensen NL, Lotan JE, Reiners WA(Eds) (1981) Fire regimes and ecosystem properties. Proceedings of the Conference, 11-15 December 1978, Honolulu, HI. USDA Forest Service, General Technical Report WO-26. (Washington DC).
41. Morsdorf F, Meier E, Kötz B, Itten KI, Dobbertin M, Allgöwer B (2004) LiDAR-based geometric reconstruction of boreal type forest stands at single tree level for forest and wildland fire management. Remote Sensing of Environment 92, 353-362. doi:10.1016/J.RSE.2004.05.013
42. Neuenschwander A (2012) Mapping vegetation structure in a wooded savanna at Freeman Ranch, TX using airborne waveform LiDAR. In 'Silvi Laser 2012: 12th International Conference on LiDAR Applications for Assessing Forest Ecosystems', 16-19 September 2012, Vancouver, BC. (Eds NCC Coops, MA Wulder) Paper SL2012-029. (Vancouver, BC) Available at http://silvilaser2012.com/wp-content/ uploads/2011/11/Silvilaser2012-Full-Proceedings.pdf [Verified 23 October 2013]
43. Neuenschwander AL, Magruder LA, Tyler M (2009) Landcover classification of small-footprint, full-waveform LiDAR data. Journal of Applied Remote Sensing 3, 033544. doi:10.1117/1.3229944
44. Peterson B, Nelson K(2011) Developing a regional canopy fuels assessment strategy using multi-scale LiDAR. In 'Proceedings of Silvi Laser 2011, 11th International Conference on LiDAR Applications for Assessing Forest Ecosystems', 16-20 October 2011, Hobart, Tas., Australia. (Ed. J Rombouts) (Conference Design Pty Ltd: Hobart) Available at http://www.iufro.org/download/file/8240/ 1742/40205-silvilaser2011- pdf/ [Verified 23 October 2013]
45. Ranson KJ, Sun G, Kovacs K, Kharuk VI (2004) Landcover attributes from ICESat GLAS data in central Siberia. In 'Geoscience and Remote Sensing Symposium, 2004. IGARSS '04. Proceedings. 2004 IEEE International', 20-24 September 2004, Anchorage, AK. Vol. 2, pp. 753-756. (The Institute of Electrical and Electronics Engineers: New York) Available at http://ieeexplore.ieee.org/ xpl/articleDetails. jsp?arnumber=1368511 [Verified 23 October 2013]
46. Reich RM, Lundquist JE, Bravo VA (2004) Spatial models for estimating fuel loads in the Black Hills, South Dakota, USA. International Journal of Wildland Fire 13, 119-129. doi:10.1071/WF02049
47. Reineke LH (1933) Perfecting a stand-density index for even-aged forests. Journal of Agricultural Research 46, 627-638.
48. Reinhardt ED, Crookston NL(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)
49. Reitberger J, Krzystek P, Stilla U (2008) Analysis of full waveform LiDAR data for the classification of deciduous and coniferous trees. International Journal of Remote Sensing 29, 1407-1431. doi:10.1080/01431160701736448
50. Riaño D, Chuvieco E, Salas J, Palacios-Orueta A, Bastarrika A (2002) Generation of fuel type maps from Landsat TM images and ancillary data in Mediterranean ecosystems. Canadian Journal of Forest Research 32, 1301-1315. doi:10.1139/X02-052
51. Riaño D, Meier E, Allgöwer B, Chuvieco E, Ustin SL (2003) Modeling airborne laser scanning data for the spatial generation of critical forest parameters in fire behavior modeling. Remote Sensing of Environment 86, 177-186. doi:10.1016/S0034-4257(03)00098-1
52. Riaño D, Chuvieco E, Condes S, Gonzalez-Matesand J, Ustin SL (2004) Generation of crown bulk density for Pinus sylvestris L. from LiDAR. Remote Sensing of Environment 92, 345-352. doi:10.1016/J.RSE.2003.12.014
53. Riaño D, Chuvieco E, Ustin SL, Salas J, Rodríguez- Pérez JR, Ribeiro LM, Viegas DX, Moreno JM, Fernández H (2007) Estimation of shrub height for fuel-type mapping combining airborne LiDAR and simultaneous color infrared ortho imaging. International Journal of Wildland Fire 16, 341-348. doi:10.1071/WF06003
54. Scott JH, Reinhardt ED (2001) Assessing crown fire potential by linking models of surface and crown fire behavior. USDA Forest Service, Rocky Mountain Research Station, Research Paper RMRS-RP-29. (Fort Collins, CO)
55. Skowronski N, Clark K, Nelson R, Hom J, Patterson M (2007) Remotely sensed measurements of forest structure and fuel loads in the Pinelands of New Jersey. Remote Sensing of Environment 108, 123-129. doi:10.1016/J.RSE.2006.09. 032
56. Skowronski NS, Clark KL, Duveneck M, Hom J (2011) Three-dimensional canopy fuel loading predicted using upward and downward sensing LiDAR systems. Remote Sensing of Environment 115, 703-714. doi:10.1016/J.RSE.2010.10.012
57. Standish JT, Manning GH, Demaershalk JP (1985) Development of biomass equations for British Columbia tree species. Canadian Forestry Service, Pacific Forest Research Center, Information Report BC-X-264. (Victoria, BC)
58. Sumnall MJ, Hill RA, Hinsley SA (2012) The estimation of forest inventory parameters from small-footprint waveform and discrete return airborne LiDAR data. In 'Silvi Laser 2012: 12th International Conference on LiDAR Applications for Assessing Forest Ecosystems', 16-19 September 2012, Vancouver, BC. (Eds NCC Coops, MA Wulder) Paper SL2012-020. (Vancouver, BC) Available at http://silvilaser2012.com/wp-content/uploads/2011/11/Silvilaser2012-Full- Proceedings.pdf [Verified 23 October 2013]
59. van Leeuwen M, Nieuwenhuis M (2010) Retrieval of forest structural parameters using LiDAR remote sensing. European Journal of Forest Research 129, 749-770. doi:10.1007/S10342-010-0381-4
60. Vaughn NR, Moskal LM, Turnblom EC (2012) Tree species detection accuracies using discrete point LiDAR and airborne waveform LiDAR. Remote Sensing 4, 377-403. doi:10.3390/RS4020377
61. Wagner W, Hollaus M, Briese C, Ducic V (2008) 3D vegetation mapping using small-footprint full-waveform airborne laser scanners. International Journal of Remote Sensing 29, 1433-1452. doi:10.1080/01431160701736398
62. Wilson BA, Ow CF, Heathcott M, Milne D, McCaffrey TM, Ghitter G, Franklin SE (1994) Landsat MSS classification of fire fuel types in Wood Buffalo National Park, northern Canada. Global Ecology and Biogeography Letters 4, 33-39. doi:10.2307/2997751
63. Zhao K, Popescu S, Meng X, Pang Y, Agca M (2011) Characterizing forest canopy structure with LiDAR composite metrics and machine learning. Remote Sensing of Environment 115, 1978-1996. doi:10.1016/J.RSE. 2011.04.001