A review of remote sensing methods for biomass feedstock production

被引:171
作者
Ahamed, T. [1 ]
Tian, L. [1 ]
Zhang, Y. [1 ]
Ting, K. C. [1 ]
机构
[1] Univ Illinois, Dept Agr & Biol Engn, Energy Biosci Inst, Urbana, IL 61801 USA
关键词
Perennial energy crops; Site-specific management; Vegetative indices; Leaf area index; Satellite imagery; Remote sensing; TROPICAL FOREST BIOMASS; LANDSAT TM DATA; ABOVEGROUND BIOMASS; RADAR BACKSCATTER; BIOPHYSICAL PROPERTIES; DENSITY-ESTIMATION; CANOPY STRUCTURE; SOIL-SALINITY; WATER-STRESS; GRAIN-YIELD;
D O I
10.1016/j.biombioe.2011.02.028
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Monitoring and maximization of bioenergy yield from biomass feedstock has recently become a critically important goal for researchers. Remote sensing represents a potential method to monitor and estimate biomass so as to increase biomass feedstock production from energy crops. This paper reviews the biophysical properties of biomass and remote sensing methods for monitoring energy crops for site-specific management. While several research studies have addressed the agronomic dimensions of this approach, more research is required on perennial energy crops in order to maximize the yield of biomass feedstock. Assessment of established methods could lead to a new strategy to monitor energy crops for the adoption of site-specific management in biomass feedstock production. In this article, satellite, aerial and ground-based remote sensing's were reviewed and focused on the spatial and temporal resolutions of imagery to adopt for site-specific management. We have concluded that the biomass yield prediction, the ground-based sensing is the most suitable to establish the calibration model and reference for aerial and satellite remote sensing. The aerial and satellite remote sensing are required for wide converge of planning and policy implementations of biomass feedstock production systems. (C) 2011 Elsevier Ltd. All rights reserved.
引用
收藏
页码:2455 / 2469
页数:15
相关论文
共 143 条
[1]  
Ahamed T, 2010, P 10 INT C PREC AGR
[2]  
Ahamed T, 2009, 095919 ASABE PM
[3]  
[Anonymous], ANN REV ENV RES
[4]  
[Anonymous], 2006, ANN EN REV
[5]  
ARC, 2000, GWA200012 ARC, P153
[6]   Estimating forest biomass using satellite radar:: an exploratory study in a temperate Australian Eucalyptus forest [J].
Austin, JM ;
Mackey, BG ;
Van Niel, KP .
FOREST ECOLOGY AND MANAGEMENT, 2003, 176 (1-3) :575-583
[7]   Remote sensing, field survey, and long-term forecasting:: an efficient combination for local assessments of forest fuels [J].
Bååth, H ;
Gällerspång, A ;
Hallsby, G ;
Lundström, A ;
Löfgren, P ;
Nilsson, M ;
Ståhl, G .
BIOMASS & BIOENERGY, 2002, 22 (03) :145-157
[8]   Forest biomass estimation over regional scales using multisource data [J].
Baccini, A ;
Friedl, MA ;
Woodcock, CE ;
Warbington, R .
GEOPHYSICAL RESEARCH LETTERS, 2004, 31 (10) :L105011-4
[9]  
Bajwa SG, 2005, T ASAE, V48, P2399, DOI 10.13031/2013.20079
[10]  
Bajwa SG, 2001, T ASAE, V44, P1965, DOI 10.13031/2013.6995