Quantifying Australian forest floristics and structure using small footprint LiDAR and large scale aerial photography

被引:57
作者
Tickle, PK
Lee, A
Lucas, RM
Austin, J
Witte, C
机构
[1] Univ Wales, Inst Geog & Earth Sci, Aberystwyth SY23 3DB, Dyfed, Wales
[2] Geosci Australia, Canberra, ACT 2601, Australia
[3] Australian Natl Univ, Sch Resources Sci & Soc, Canberra, ACT 0200, Australia
[4] CRC Greenhouse Accounting, Canberra, ACT 0200, Australia
[5] Queensland Dept Nat Resources & Mines, Forest Ecosyst Res & Assessment, Resource Sci Ctr, Indooroopilly, Qld 4068, Australia
基金
澳大利亚研究理事会;
关键词
forests; LiDAR; aerial photography; floristics; structure; monitoring; Australia;
D O I
10.1016/j.foreco.2005.11.021
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Light detection and ranging (LiDAR) data and large scale (1:4000) photography (LSP) were investigated for their potential to quantify the floristics and structure of mixed species forests near Injune, central east Queensland, and to scale these up to the region for purposes of baseline assessment and on-going monitoring. For a 220,000 hectare (ha) area, LiDAR and LSP were acquired over 150 500 m x 150 m (7.5 ha) primary sampling units (PSUs) located on a similar to 4 km systematic grid. Based on LSP interpretation, 292 species combinations were observed, although forests were dominated or co-dominated primarily by Callitris glaucophylla, Eucalyptus melanaphloia, Eucalyptus populnea and Angophora Leiocarpa. Comparisons with species distributions mapped using LSP and in the field suggested a 79% correspondence for dominant species. Robust relationships were observed between LiDAR and field measurements of individual tree (r(2) = 0.91, S.E. = 1.34 m, n = 100) and stand (r(2) = 0.84, S.E. = 2.07 m, n = 32) height. LiDAR-derived estimates of plot level foliage/branch projected cover (FBPC), defined by the percentage of returns > 2 m, compared well (r(2) of 0.74, S.E. = 8.1%, n = 29) with estimates based on field transects. When translated to foliage projected cover (FPC), a close correspondence with field measurements (r(2) = 0.62, S.E. = 6.2%, n = 29) was observed. Using these relationships, floristics and both height and FPC distributions were estimated for forests contained with the PSU grid and extrapolated to the study area. Comparisons with National Forest Inventory (NFI), National Vegetation Information System (NVIS) and Queensland Herbarium data suggested that sampling using LSP and LiDAR aggregated to the landscape provided similar estimates at the broad level but allowed access to a permanent and more detailed record. Observed differences were attributed to different scales of data acquisition and mapping. The cost of survey was also reduced compared to more traditional methods. The method outlined in the paper has relevance to national forest monitoring initiatives, such as the Continental Forest Monitoring Framework currently being evaluated in Australia. (c) 2005 Elsevier B.V. All rights reserved.
引用
收藏
页码:379 / 394
页数:16
相关论文
共 49 条
[1]  
Aldred A., 1985, PIX51 CAN FOR SERV P, P62
[2]  
[Anonymous], 1993, SAMPLING METHODS MUL
[3]  
[Anonymous], AUSTR ENV
[4]  
*AUSTR GREENH OFF, 2000, NAT GREENH GAS INV L
[5]   Quantifying uncertainty in estimates of C emissions from above-ground biomass due to historic land-use change to cropping in Australia [J].
Barrett, DJ ;
Galbally, IE ;
Graetz, RD .
GLOBAL CHANGE BIOLOGY, 2001, 7 (08) :883-902
[6]  
*BUR RUR SCI, 2003, CONT FOR MON FRAM AU
[7]   Growth and carbon stock change in eucalypt woodlands in northeast Australia: ecological and greenhouse sink implications [J].
Burrows, WH ;
Henry, BK ;
Back, PV ;
Hoffmann, MB ;
Tait, LJ ;
Anderson, ER ;
Menke, N ;
Danaher, T ;
Carter, JO ;
McKeon, GM .
GLOBAL CHANGE BIOLOGY, 2002, 8 (08) :769-784
[8]  
CARNAHAN JA, 1990, VEGETATION ATLAS AUS
[9]  
*COMM AUSTR, 2002, IMPL MONTR PROC CRIT
[10]   Vegetation classification of the riparian zone along the Brisbane River, Queensland, Australia, using light detection and ranging (lidar) data and forward looking digital video [J].
Dowling, R ;
Accad, A .
CANADIAN JOURNAL OF REMOTE SENSING, 2003, 29 (05) :556-563