STAND VOLUMES ESTIMATE Eucalyptus spp. PLANTATIONS IN FORESTS USING HYPERSPECTRAL AND TOPOGRAPHIC DATA

被引:19
作者
Canavesi, Vanessa
Ponzoni, Flavio Jorge
Valeriano, Marcio Morisson
机构
来源
REVISTA ARVORE | 2010年 / 34卷 / 03期
关键词
Vegetation anisotropy; Biophysical parameters and SRTM; LEAF-AREA INDEX; ABOVEGROUND BIOMASS; REFLECTANCE; GROWTH;
D O I
10.1590/S0100-67622010000300018
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
The availability of orbital hyperspectral data has brought new perspectives to both academic and corporative sectors solving demands in forestry science. The main objective of this work was to evaluate the potential of Hyperion EO-1 hyperspectral data to quantify the biophysical timber volume in Eucalyptus spp stands and the effect of hill shading in that quantification. For this, the correlations between spectral data and timber volume were performed following the use of Multiple Linear regression models as the descriptors of the relationships established. The relief effect on the Eucalyptus spp. canopy reflectance was taken into account. The Hyperion EO-1 data were converted to BRF surface values, which were considered the basis glare entire work. The study area was located in the municipality of Capao Bonito (the State of Silo Paulo, Brazil) and included Eucalyptus spp. stands managed by the Votorantim Papel e Celulose company (VCP). Spectral samples were collected in different topographic conditions. In the establishment of the relationship with timber volume, the vegetation indices estimated using hyperspectral data resulted in models with higher R2 when considering the topographic illumination effect showing higher applicability potential of this data.
引用
收藏
页码:539 / 549
页数:11
相关论文
共 37 条
[1]  
BECK R, 2006, EO 1 USER GUIDE
[2]  
BOLFE EL, 2003, S BRASILEIRO SENSORI, V11, P2671
[3]   SPRING: Integrating remote sensing and GIS by object-oriented data modelling [J].
Camara, G ;
Souza, RCM ;
Freitas, UM ;
Garrido, J .
COMPUTERS & GRAPHICS, 1996, 20 (03) :395-403
[4]   A FRAMEWORK FOR MONITORING CROP GROWTH BY COMBINING DIRECTIONAL AND SPECTRAL REMOTE-SENSING INFORMATION [J].
CLEVERS, JGPW ;
BUKER, C ;
VANLEEUWEN, HJC ;
BOUMAN, BAM .
REMOTE SENSING OF ENVIRONMENT, 1994, 50 (02) :161-170
[5]   Preprocessing EO-1 Hyperion hyperspectral data to support the application of agricultural indexes [J].
Datt, B ;
McVicar, TR ;
Van Niel, TG ;
Jupp, DLB ;
Pearlman, JS .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (06) :1246-1259
[6]   A multi-scale approach to mapping effective Leaf Area Index in Boreal Picea mariana stands using high spatial resolution CASI imagery [J].
Fernandes, R ;
Miller, JR ;
Hu, B ;
Rubinstein, IG .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2002, 23 (18) :3547-3568
[7]   Predictive relations of tropical forest biomass from Landsat TM data and their transferability between regions [J].
Foody, GM ;
Boyd, DS ;
Cutler, MEJ .
REMOTE SENSING OF ENVIRONMENT, 2003, 85 (04) :463-474
[8]  
Franklin S.E., 2001, Remote Sensing for Sustainable Forest Management
[9]  
GALVAO LS, 2009, S BRASILEIRO SENSORI, V4, P1095
[10]   A NARROW-WAVEBAND SPECTRAL INDEX THAT TRACKS DIURNAL CHANGES IN PHOTOSYNTHETIC EFFICIENCY [J].
GAMON, JA ;
PENUELAS, J ;
FIELD, CB .
REMOTE SENSING OF ENVIRONMENT, 1992, 41 (01) :35-44