Single tree biomass modelling using airborne laser scanning

被引:48
作者
Kankare, Ville [1 ]
Raety, Minna [2 ]
Yu, Xiaowei [3 ]
Holopainen, Markus [1 ]
Vastaranta, Mikko [1 ]
Kantola, Tuula [1 ]
Hyyppa, Juha [3 ]
Hyyppa, Hannu [4 ,5 ]
Alho, Petteri [6 ]
Viitala, Risto [7 ]
机构
[1] Univ Helsinki, Dept Forest Sci, FIN-00014 Helsinki, Finland
[2] Joint Res Ctr, Inst Environm & Sustainabil, Forest Resources & Climate Unit, Ispra, Italy
[3] Finnish Geodet Inst, Dept Remote Sensing & Photogrammetry, Masala, Finland
[4] Aalto Univ, Res Inst Measuring & Modelling Built Environm, Helsinki, Finland
[5] Univ Appl Sci Civil Engn & Bldg Serv, Helsinki Metropolia, Helsinki, Finland
[6] Univ Turku, Dept Geog & Geol, SF-20500 Turku, Finland
[7] Univ Appl Sci, HAMK, Helsinki, Finland
关键词
Airborne laser scanning; Aboveground; Biomass; Point metrics; Modelling; Single tree; SMALL-FOOTPRINT LIDAR; ABOVEGROUND BIOMASS; FOREST BIOMASS; NORWAY SPRUCE; STEM VOLUME; SCOTS PINE; HEIGHT; IMPUTATION; EQUATIONS; VARIABLES;
D O I
10.1016/j.isprsjprs.2013.08.008
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Accurate forest biomass mapping methods would provide the means for e.g. detecting bioenergy potential, biofuel and forest-bound carbon. The demand for practical biomass mapping methods at all forest levels is growing worldwide, and viable options are being developed. Airborne laser scanning (ALS) is a promising forest biomass mapping technique, due to its capability of measuring the three-dimensional forest vegetation structure. The objective of the study was to develop new methods for tree-level biomass estimation using metrics derived from ALS point clouds and to compare the results with field references collected using destructive sampling and with existing biomass models. The study area was located in Evo, southern Finland. ALS data was collected in 2009 with pulse density equalling approximately 10 pulses/m(2). Linear models were developed for the following tree biomass components: total, stem wood, living branch and total canopy biomass. ALS-derived geometric and statistical point metrics were used as explanatory variables when creating the models. The total and stem biomass root mean square error per cents equalled 26.3% and 28.4% for Scots pine (Pinus sylvestris L.), and 36.8% and 27.6% for Norway spruce (Picea abies (L.) H. Karst.), respectively. The results showed that higher estimation accuracy for all biomass components can be achieved with models created in this study compared to existing allometric biomass models when ALS-derived height and diameter were used as input parameters. Best results were achieved when adding field-measured diameter and height as inputs in the existing biomass models. The only exceptions to this were the canopy and living branch biomass estimations for spruce. The achieved results are encouraging for the use of ALS-derived metrics in biomass mapping and for further development of the models. (C) 2013 International Society for Photogrammetry and Remote Sensing, Inc. (ISPRS) Published by Elsevier B.V. All rights reserved.
引用
收藏
页码:66 / 73
页数:8
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