Arid
DOI10.1016/j.rse.2014.01.024
Airborne multi-temporal L-band polarimetric SAR data for biomass estimation in semi-arid forests
Tanase, Mihai A.1; Panciera, Rocco1; Lowell, Kim1; Tian, Siyuan1; Hacker, Jorg M.2; Walker, Jeffrey P.3
通讯作者Tanase, Mihai A.
来源期刊REMOTE SENSING OF ENVIRONMENT
ISSN0034-4257
EISSN1879-0704
出版年2014
卷号145页码:93-104
英文摘要

Using the airborne Polarimetric L-band Imaging Synthetic aperture radar (PUS) the impact of high revisit cycle and full polarimetric acquisitions on biomass retrieval was investigated by means of backscatter-based multi-temporal methods. Parametric and non-parametric models were used to relate reference biomass levels obtained from field plot measurements and high point density lidar data to backscatter intensities or polarimetric target decomposition components. Single-date retrieval using multiple independent variables provided lower estimation errors when compared to models using one independent variable with errors decreasing by 2% to 15%. The multi-temporal aggregation of daily biomass estimates did not improve the overall retrieval accuracy but provided more reliable estimates with respect to single-date methods. Backscatter intensities improved estimation accuracies up to 10% compared to polarimetric target decomposition components. Using all four polarizations increased the estimation accuracy marginally (2%). when compared to a dual-polarized system. The biomass estimation error was considerably reduced (up to 30%) only by decreasing the spatial resolution and was related to decreasing forest variability with increasing pixel size. These results indicate that, at least in semi-arid areas, future L-band missions would not significantly improve biomass estimation accuracy using backscatter-based modeling approaches despite their better spatial resolution, higher revisit cycles and the availability of fully polarimetric information. (C) 2014 Elsevier Inc All rights reserved.


英文关键词Forest biomass L-band radar Multi-temporal Polarimetric decomposition Random forest Forest variability
类型Article
语种英语
国家Australia
收录类别SCI-E
WOS记录号WOS:000335113200009
WOS关键词ESTIMATING ABOVEGROUND BIOMASS ; BOREAL FOREST ; RADAR BACKSCATTER ; SCATTERING-MODEL ; PARAMETER-ESTIMATION ; SPATIAL VARIABILITY ; TROPICAL FORESTS ; STEM VOLUME ; CLASSIFICATION ; RETRIEVAL
WOS类目Environmental Sciences ; Remote Sensing ; Imaging Science & Photographic Technology
WOS研究方向Environmental Sciences & Ecology ; Remote Sensing ; Imaging Science & Photographic Technology
资源类型期刊论文
条目标识符http://119.78.100.177/qdio/handle/2XILL650/184718
作者单位1.Univ Melbourne, Cooperat Res Ctr Spatial Informat, Melbourne, Vic 3010, Australia;
2.Flinders Univ S Australia, Sch Environm, Airborne Res Australia, Adelaide, SA, Australia;
3.Monash Univ, Dept Civil Engn, Clayton, Vic 3800, Australia
推荐引用方式
GB/T 7714
Tanase, Mihai A.,Panciera, Rocco,Lowell, Kim,et al. Airborne multi-temporal L-band polarimetric SAR data for biomass estimation in semi-arid forests[J],2014,145:93-104.
APA Tanase, Mihai A.,Panciera, Rocco,Lowell, Kim,Tian, Siyuan,Hacker, Jorg M.,&Walker, Jeffrey P..(2014).Airborne multi-temporal L-band polarimetric SAR data for biomass estimation in semi-arid forests.REMOTE SENSING OF ENVIRONMENT,145,93-104.
MLA Tanase, Mihai A.,et al."Airborne multi-temporal L-band polarimetric SAR data for biomass estimation in semi-arid forests".REMOTE SENSING OF ENVIRONMENT 145(2014):93-104.
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