DOI: 10.1016/j.jag.2014.03.005
Scopus记录号: 2-s2.0-84904463486
论文题名: Estimation of aboveground biomass in Mediterranean forestsby statistical modelling of ASTER fraction images
作者: Fernández-Manso O ; , Fernández-Manso A ; , Quintano C
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2014
卷: 31, 期: 1 起始页码: 45
结束页码: 56
语种: 英语
英文关键词: ASTER
; Biomass estimation
; Forest inventory
; Mediterranean pine
; Multiple linear regression
; Spectral mixture analysis
Scopus关键词: ASTER
; biomass
; estimation method
; forest inventory
; image analysis
; NDVI
; regression analysis
; spatial distribution
; statistical analysis
; Spain
英文摘要: Aboveground biomass (AGB) estimation from optical satellite data is usually based on regression mod-els of original or synthetic bands. To overcome the poor relation between AGB and spectral bands dueto mixed-pixels when a medium spatial resolution sensor is considered, we propose to base the AGBestimation on fraction images from Linear Spectral Mixture Analysis (LSMA). Our study area is a man-aged Mediterranean pine woodland (Pinus pinaster Ait.) in central Spain. A total of 1033 circular fieldplots were used to estimate AGB from Advanced Spaceborne Thermal Emission and Reflection Radiome-ter (ASTER) optical data. We applied Pearson correlation statistics and stepwise multiple regression toidentify suitable predictors from the set of variables of original bands, fraction imagery, Normalized Dif-ference Vegetation Index and Tasselled Cap components. Four linear models and one nonlinear modelwere tested. A linear combination of ASTER band 2 (red, 0.630-0.690 μm), band 8 (short wave infrared 5,2.295-2.365 μm) and green vegetation fraction (from LSMA) was the best AGB predictor (R2 adj= 0.632, theroot-mean-squared error of estimated AGB was 13.3 Mg ha-1(or 37.7%), resulting from cross-validation), rather than other combinations of the above cited independent variables. Results indicated that using ASTER fraction images in regression models improves the AGB estimation in Mediterranean pine forests.The spatial distribution of the estimated AGB, based on a multiple linear regression model, may be usedas baseline information for forest managers in future studies, such as quantifying the regional carbonbudget, fuel accumulation or monitoring of management practices. © 2014 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79774
Appears in Collections: 气候变化事实与影响
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作者单位: Civil Protection Agency, Castilla y León Government, Valladolid, Spain; Agrarian Engineering and Sciences Department, University of León, Campus of Ponferrada, León, Spain; Electronic Technology Department, University of Valladolid, Spain; Sustainable Forest Management Research Institute, University of Valladolid-INIA, Spain
Recommended Citation:
Fernández-Manso O,, Fernández-Manso A,, Quintano C. Estimation of aboveground biomass in Mediterranean forestsby statistical modelling of ASTER fraction images[J]. International Journal of Applied Earth Observation and Geoinformation,2014-01-01,31(1)