Forest biomass mapping from lidar and radar synergies

被引:138
|
作者
Sun, Guoqing [1 ]
Ranson, K. Jon [2 ]
Guo, Z. [3 ]
Zhang, Z. [4 ]
Montesano, P. [5 ]
Kimes, D. [2 ]
机构
[1] Univ Maryland, Dept Geog, College Pk, MD 20742 USA
[2] NASA, Biospher Sci Branch, Goddard Space Flight Ctr, Greenbelt, MD USA
[3] Chinese Acad Sci, State Key Lab Remote Sensing, Inst Remote Sensing Applicat, Beijing 100101, Peoples R China
[4] Beijing Normal Univ, Sch Geog, Beijing 100875, Peoples R China
[5] Sci Syst & Applicat Inc, Lanham, MD 20706 USA
基金
中国国家自然科学基金;
关键词
Forest biomass; DESDynI mission; Lidar waveform; LVIS; SRTM; PALSAR; InSAR; TOPOGRAPHY MISSION; MANGROVE FORESTS; VEGETATION; BACKSCATTER; INVENTORY; INVERSION; ECOSYSTEM; HEIGHT; FUSION;
D O I
10.1016/j.rse.2011.03.021
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The use of lidar and radar instruments to measure forest structure attributes such as height and biomass at global scales is being considered for a future Earth Observation satellite mission, DESDynI (Deformation, Ecosystem Structure, and Dynamics of Ice). Large footprint lidar makes a direct measurement of the heights of scatterers in the illuminated footprint and can yield accurate information about the vertical profile of the canopy within lidar footprint samples. Synthetic Aperture Radar (SAR) is known to sense the canopy volume, especially at longer wavelengths and provides image data. Methods for biomass mapping by a combination of lidar sampling and radar mapping need to be developed. In this study, several issues in this respect were investigated using aircraft borne lidar and SAR data in Howland, Maine, USA. The stepwise regression selected the height indices rh50 and rh75 of the Laser Vegetation Imaging Sensor (LVIS) data for predicting field measured biomass with a R-2 of 0.71 and RMSE of 3133 Mg/ha. The above-ground biomass map generated from this regression model was considered to represent the true biomass of the area and was used as a reference map since no better biomass map exists for the area. Random samples were taken from the biomass map and the correlation between the sampled biomass and co-located SAR signature was studied. The best models were used to extend the biomass from lidar samples into all forested areas in the study area, which mimics a procedure that could be used for the future DESDYnI mission. It was found that depending on the data types used (quad-pol or dual-pol) the SAR data can predict the lidar biomass samples with R-2 of 0.63-0.71. RMSE of 32.0-28.2 Mg/ha up to biomass levels of 200-250 Mg/ha. The mean biomass of the study area calculated from the biomass maps generated by lidar-SAR synergy was within 10% of the reference biomass map derived from LVIS data. The results from this study are preliminary, but do show the potential of the combined use of lidar samples and radar imagery for forest biomass mapping. Various issues regarding lidar/radar data synergies for biomass mapping are discussed in the paper. (C) 2011 Elsevier Inc. All rights reserved.
引用
收藏
页码:2906 / 2916
页数:11
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