National Forest Aboveground Biomass Mapping from ICESat/GLAS Data and MODIS Imagery in China

Remote Sensing

Hong Chi¹  Guoqing Sun⁵  Jinliang Huang¹  Zhifeng Guo²  Wenjian Ni²  Anmin Fu³  Xiangming Xiao⁴  Jinwei Dong⁴ 

[1] Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430071, China; E-Mail:;Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100732, China; E-Mails:;Academy of Forest Inventory and Planning, State Forestry Administration, Beijing 100714, China; E-Mail:;Institute of Geodesy and Geophysics, Chinese Academy of Sciences, Wuhan 430071, China; E-Mail;Department of Geographical Sciences, University of Maryland, College Park, MD 20742, USA; E-Mail:

关键词: forest aboveground biomass;    ICESat/GLAS;    large footprint LiDAR;    MODIS;    forest inventory data;    China;   

DOI  :  10.3390/rs70505534

来源: mdpi

【 摘 要 】

Forest aboveground biomass (AGB) was mapped throughout China using large footprint LiDAR waveform data from the Geoscience Laser Altimeter System (GLAS) onboard NASA’s Ice, Cloud, and land Elevation Satellite (ICESat), Moderate Resolution Imaging Spectro-radiometer (MODIS) imagery and forest inventory data. The entire land of China was divided into seven zones according to the geographic characteristics of the forests. The forest AGB prediction models were separately developed for different forest types in each of the seven forest zones at GLAS footprint level from GLAS waveform parameters and biomass derived from height and diameter at breast height (DBH) field observation. Some waveform parameters used in the prediction models were able to reduce the effects of slope on biomass estimation. The models of GLAS-based biomass estimates were developed by using GLAS footprints with slopes less than 20° and slopes ≥ 20°, respectively. Then, all GLAS footprint biomass and MODIS data were used to establish Random Forest regression models for extrapolating footprint AGB to a nationwide scale. The total amount of estimated AGB in Chinese forests around 2006 was about 12,622 Mt vs. 12,617 Mt derived from the seventh national forest resource inventory data. Nearly half of all provinces showed a relative error (%) of less than 20%, and 80% of total provinces had relative errors less than 50%.

【 授权许可】

CC BY   
© 2015 by the authors; licensee MDPI, Basel, Switzerland.