The importance of spatial detail: Assessing the utility of individual crown information and scaling approaches for lidar-based biomass density estimation

Remote Sensing of Environment

Volumn 168, Issue , 2015, Pages 102-112

  Duncanson, L I ^a   Dubayah, R O ^a   Cook, B D ^b   Rosette, J ^b   Parker, G ^c  

^a UNIVERSITY OF MARYLAND   (United States)

^b NASA GODDARD SPACE FLIGHT CENTER   (United States)

^c SMITHSONIAN ENVIRONMENTAL RESEARCH CENTER   (United States)

Author keywords

Biomass; Carbon; Crown delineation; Forest; Individual tree structure; Lidar

Indexed keywords

BIOMASS; CARBON; MAPPING; OPTICAL RADAR; REMOTE SENSING;

ABOVE GROUND BIOMASS; ALGORITHM DEVELOPMENT; ALLOMETRIC EQUATIONS; COMPUTER PROCESSING POWER; CROWN DELINEATION; FOREST; INDIVIDUAL TREE; LOBLOLLY PINE PLANTATIONS;

FORESTRY;

ABOVEGROUND BIOMASS; ALGORITHM; ALLOMETRY; CANOPY ARCHITECTURE; CONIFEROUS TREE; DECIDUOUS FOREST; DRY DENSITY; EVERGREEN FOREST; FOREST CANOPY; INDIVIDUAL-BASED MODEL; LIDAR; PLANTATION FORESTRY; REMOTE SENSING;

BIOMASS; FORESTRY; INFORMATION RETRIEVAL; MAPPING; REMOTE SENSING;

CONIFEROPHYTA; PINUS TAEDA;

EID: 84936949880     PISSN: 00344257     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.rse.2015.06.021     Document Type: Article

References (62)

1. Abdi H. Partial least squares regression and projection on latent structure regression (PLS regression). Wiley Interdisciplinary Reviews: Computational Statistics 2010, 2(1):97-106.
2. Asner G.P. Tropical forest carbon assessment: Integrating satellite and airborne mapping approaches. Environmental Research Letters 2009, 4(3):034009.
3. Asner G.P., Hughes R.F., Mascaro J., Uowolo A.L., Knapp D.E., Jacobson J., et al. High-resolution carbon mapping on the million-hectare Island of Hawaii. Froniers in Ecology 2011, 9(8):434-439.
4. Asner G.P., Mascaro J. Mapping tropical forest carbon: Calibrating plot estimates to a simple LiDAR metric. Remote Sensing of Environment 2014, 140:614-624.
5. Baccini A., Goetz S.J., Walker W.S., Laporte N.T., Sun M., Sulla-Menashe D., et al. Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Climate Change 2012, 2:182-185.
6. Baccini A., Laporte N., Goetz S., Sun M., Dong H. A first map of tropical Africa's above-ground biomass derived from satellite imagery. Environmental Research Letters 2008, 3(4):045011.
7. Bortolot Z.J., Wynne R.H. Estimating forest biomass using small footprint data: An individual tree-based approach that incorporates training data. ISPRS Journal of Photogrammetry and Remote Sensing 2005, 59(6):342-360.
8. Boudreau J., Nelson R.F., Margolis H.A., Beaudoin A., Guindon L., Kimes D.S. Regional aboveground forest biomass using airborne and spaceborne LiDAR in Québec. Remote Sensing of Environment 2008, 112(10):3876-3890.
9. Breidenbach J., Næsset E., Lien V., Gobakken T., Solberg S. Prediction of species specific forest inventory attributes using a nonparametric semi-individual tree crown approach based on fused airborne laser scanning and multispectral data. Remote Sensing of Environment 2010, 114(4):911-924.
10. Chojnacky D.C., Heath L.S., Jenkins J.C. Updated generalized biomass equations for North American tree species. Forestry 2014, 87:129-151.
11. Clark A.I., Phillips D., Frederick D. Weight, volume, and physical properties of major hardwood species in the Gulf and Atlantic Coastal Plains. USDA Forest Service Research Papers 1985, SE-250.
12. Clark A.I., Phillips D., Frederick D. Weight, volume, and physical properties of major hardwood species in the upland south. USDA Forest Service Research Papers 1986, SE-257.
13. Clark A.I., Schroeder J. Weight, volume, and physical properties of major hardwood species in the southern Appalachian mountains. USDA Forest Service Research Papers 1986, SE-153.
14. Cook B.D., Corp L.A., Nelson R.F., Middleton E.M., Morton D.C., McCorkel J.T., et al. NASA Goddard's LiDAR, hyperspectral and thermal (G-LiHT) airborne imager. Remote Sensing 2013, 5(8):4045-4066.
15. Coops N.C., Hilker T., Wulder M.A., St-nge B., Newnham G., Siggens A., et al. Estimating canopy structure of Douglas-fir forest stands from discrete-return LiDAR. Trees: Structure and Function 2007, 21(3):295-310.
16. Corbera E., Schroeder H. Governing and implementing REDD+. Environmental Science & Policy 2011, 14(2):89-99.
17. Domke G.M., Woodall C.W., Smith J.E., Westfall J.A., McRoberts R.E. Consequences of alternative tree-level biomass estimation procedures on U.S. forest carbon stock estimates. Forest Ecology and Management 2012, 270:108-116.
18. Domke G.M., Woodall C.W., Smith J.E., Westfall J.A., McRoberts R.E. Forest Ecology & Management 2012, 270:108-116.
19. Drake J.B., Dubayah R.O., Knox R.G., Clark D.B., Blair J.B. Sensitivity of large-footprint LiDAR to canopy structure and biomass in a neotropical rainforest. Remote Sensing of Environment 2002, 81:378-392.
20. Dubayah R.O., Drake J.B. LiDAR remote sensing for forestry. Journal of Forestry 2000, 98:44-46.
21. Duncanson L.I., Cook B.D., Hurtt G.C., Dubayah R.O. An efficient, multi-layered canopy delineation algorithm for mapping individual tree structure across multiple ecosystems. Remote Sensing of Environment 2014, 154:378-386.
22. Duncanson L.I., Niemann K.O., Wulder M.A. Integration of GLAS and Landsat TM data for aboveground biomass estimation. Canadian Journal of Remote Sensing 2010, 36(2):129-141.
23. Fatemi F.R., Yanai R.D., Hamburg S.P., Vadeboncoeur M.A., Arthur M.A., Briggs R.D., et al. Allometric equations for young northern hardwoods: The importance of age-specific equations for estimating aboveground biomass. Canadian Journal of Forest Research 2011, 41(4):881-891.
24. Ferster C.J., Coops N.C., Trofymow J.A. Aboveground large tree mass estimation in a coastal forest in British Columbia using plot-level metrics and individual tree detection from lidar 2009.
25. Goetz S.J., Baccini A., Laporte N., Johns T., Walker W.S., Kellndorfer J.M., et al. Mapping and monitoring carbon stocks with satellite observations: A comparison of methods. Carbon Balance and Management 2009, 10.1186/1750-0680-1184-1182.
26. Goetz S.G., Dubayah R.O. Advances in remote sensing technology and implications for monitoring, reporting and verifying forest carbon stocks and emissions. Carbon Management 2011, 2:231-244.
27. Houghton R.A., Lawrence K.T., Hackler J.L., Brown S. The spatial distribution of forest biomass in the Brazilian Amazon: A comparison of estimates. Global Change Biology 2001, 7(7):731-746.
28. Jenkins J.C., Chojnacky C.D., Heath L.S., Birdsey R.A. National scale biomass estimators for United States tree species. Forest Science 2003, 49:12-35.
29. Kaartinen H., Hyyppä J., Yu X., Vastaranta M., Hyyppä H., Kukko A., et al. An international comparison of individual tree detection and extraction using airborne laser scanning. Remote Sensing 2012, 4(4):950-974.
30. Lefsky M.A., Cohen W.B., Acker S.A., Parker G.G., Spies T.A., Harding D. Lidar remote sensing of the canopy structure and biophysical properties of Douglas-fir western hemlock forests. Remote Sensing of Environment 1999, 70:339-361.
31. Lefsky M.A., Cohen W.B., Harding D.J., Parker G.G., Acker S.A., Gower S.T. Lidar remote sensing of above-ground biomass in three biomes. Global Ecology and Biogeography 2003, 11(5):393-399.
32. Lefsky M.A., Harding D., Cohen W.B., Parker G., Shugart H.H. Surface Lidar remote sensing of basal area and biomass in deciduous forests of eastern Maryland, USA. Remote Sensing of Environment 1999, 67:83-98.
33. Lefsky M.A., Harding D.J., Keller M., Cohen W.B., Carabajal C.C., Espirito-Santo F.D., et al. Estimates of forest canopy height and aboveground biomass using ICESat. Geophysical Research Letters 2005, 32. 10.1029/2005GL023971.
34. Lim K., Trietz P., Wulder M.A., St-Onge B., Flood M. LiDAR remote sensing of forest structure. Progress in Physical Geography 2003, 72:88-106.
35. Martin J., Kloeppel B., Schaefer T., Kimbler D., McNulty S. Aboveground biomass and nitrogen allocation of ten deciduous southern Appalachian tree species. Canadian Journal of Forest Research 1998, 28:1648-1659.
36. Monteith D. Whole tree weight tables for New York State. AFRI Research Repository, No. 40 1979, University of New York College of Environmental Science and Forestry, Applied Forest Research Institute.
37. Næsset E. Determination of mean tree height of forest stands using airborne laser scanner data. ISPRS Journal of Photogrammetry and Remote Sensing 1997, 52(2):49-56.
38. Næsset E. Accuracy of forest inventory using airborne laser scanning: Evaluating the first Nordic full-scale operational project. Scandinavian Journal of Forest Research 2004, 19(6):554-557.
39. Naidu S., Delucia E., Thomas R. Estimating weights of loblolly pine trees and their components in natural stands and plantations in central Mississippi. Mississippi Agricultural and Forest Explorations Station Technical Bulletin 1998, 73.
40. Ni-Meister W., Lee S.Y., Strahler A.H., Woodcock C.E., Schaaf C., Yao T.A., et al. Assessing general relationships between aboveground biomass and vegetation structure parameters for improved carbon estimate from lidar remote sensing. Journal of Geophysical Research-Biogeosciences 2010, 115.
41. Pan Y., Birdsey R.A., Fang J., Houghton R., Kauppi P.E., Kurz W.A., et al. A large and persistent carbon sink in the world's forests. Science 2011, 333(6045):988-993.
42. Pastor J., Aber J.C., Melilo J.M. Biomass prediction using generalized allometric regressions for some northeast tree species. Forest Ecology and Management 1984, 7(4):265-274.
43. Pflugmacher D., Cohen W., Kennedy R., Lefsky M. Regional applicability of forest height and aboveground biomass models for the geoscience laser altimeter system. Forest Science 2008, 54:647-657.
44. Phillips D. Predicted total-tre biomass of understory hard-woods. USDA Forest Service Research Papers 1981, SE-223.
45. Popescu S.C., Wynne R.H., Nelson R.F. Measuring individual tree crown diameter with lidar and assessing its influence on estimating forest volume and biomass. Canadian Journal of Remote Sensing 2003, 29(5):564-577.
46. Popescu S.C., Zhao K. A voxel-based lidar method for estimating crown base height for deciduous and pine trees. Remote Sensing of Environment 2008, 112(3):767-781.
47. Reitberger J., Schnörr C.I., Krzystek P., Stilla U. 3D segmentation of single trees exploiting full waveform LIDAR data. ISPRS Journal of Photogrammetry and Remote Sensing 2009, 64(6):561-574.
48. Ruiz L.A., Hermosilla T., Mauro F., Godino M. Analysis of the influence of plot size and LiDAR density on forest structure attribute estimates. Forests 2014, 5(5):936-951.
49. Saatchi S.S., Harris N.L., Brown S., Lefsky M., Mitchard E.T.A., Salas W., et al. Benchmark map of forest carbon stocks in tropical regions across three continents. PNAS 2011, 108(24):9899-9904.
50. Siccama T.G., Hamburg S.P., Arthr M.A., Yanai R.D., Bormann F., Likens G.E. Corrections to allometric equations and plant tissue chemistry for Hubbard Brook Experimental Forest. Ecology 1994, 75:246-248.
51. SIGEO Smithsonian Institution Global Earth Observatories Available online at:. http://www.sigeo.si.edu/.
52. Suarez J.C. The use of small footprint airborne LiDAR for estimation of individual tree parameters in Sitka spruce stands. Challenges and opportunities for the world's forests in the 21st century Spring, 2013, 81. T. Fenning (Ed.).
53. Swatantran A., Dubayah R., Roberts D., Hofton M., Blair J.B. Mapping biomass and stress in the Sierra Nevada using lidar and hyperspectral data fusion. Remote Sensing of Environment 2011, 115(11):2917-2930.
54. Van Aardt J.A., Wynne R.H., Oderwald R.G. Forest volume and biomass estimation using small-footprint lidar-distributional parameters on a per-segment basis. Forest Science 2006, 52(6):2006.
55. Vastaranta M., Holopainen M., Yu X., Haapanen R., Melkas T., Hyyppa J., et al. Individual tree detection and area-based approach in retrieval of forest inventory characteristics from low-pulse airborne laser scanning data. Photogrammetric Journal of Finland 2011, 22(2):1-13.
56. Williams R.A., McClenahen J.R. Biomass prediction equations for seedlings, sprouts, and saplings of ten central hardwood species. Forest Science 1984, 30:523-527.
57. Wulder M.A., Bater C.W., Coops N.C., Hilker T., White J.C. The role of LiDAR in sustainable forest management. The Forestry Chronicle 2008, 84(6):808-826.
58. Wulder M.A., Seeman D. Forest inventory height update through the integration of lidar data with segmented Landsat imagery. Canadian Journal of Remote Sensing 2003, 29(5):536-543.
59. Wulder M.A., White J.C., Nelson R.F., Naesset E., Orka H.O., Coops N.C., et al. Lidar sampling for large-area forest characterization: A review. Remote Sensing of Environment 2012, 121(1):196-209.
60. Zhao F., Guo Q., Kelly M. Allometric equation choice impacts lidar-based forest biomass estimates: A case study from the Sierra National Forest, CA. Agricultural and Forest Meteorology 2012, 165:64-72.
61. Zhao K., Popescu S., Nelson R. Lidar remote sensing of forest biomass: A scale-invariant estimation approach using airborne lasers. Remote Sensing of Environment 2009, 113(1):182-196.
62. Zolkos S.G., Goetz S.J., Dubayah R. A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote Sensing of Environment 2013, 128:289-298.