Application of Physically-Based Slope Correction for Maximum Forest Canopy Height Estimation Using Waveform Lidar across Different Footprint Sizes and Locations: Tests on LVIS and GLAS

Remote Sensing

Taejin Park²  Robert E. Kennedy²  Sungho Choi²  Jianwei Wu²  Michael A. Lefsky¹  Jian Bi²  Joshua A. Mantooth²  Ranga B. Myneni² 

[1] Center for Ecological Analysis of Lidar, Natural Resource Ecology Laboratory, Colorado State University, Fort Collins, CO 80523, USA; E-Mail:;Department of Earth and Environment, Boston University, 675 Commonwealth Avenue, Boston, MA 02215, USA; E-Mails:

关键词: remote sensing;    Geoscience Laser Altimeter System (GLAS);    Laser Vegetation Imaging Sensor (LVIS);    Light Detection and Ranging (LiDAR);    maximum forest canopy height;    slope effect correction;   

DOI  :  10.3390/rs6076566

来源: mdpi

【 摘 要 】

Forest canopy height is an important biophysical variable for quantifying carbon storage in terrestrial ecosystems. Active light detection and ranging (lidar) sensors with discrete-return or waveform lidar have produced reliable measures of forest canopy height. However, rigorous procedures are required for an accurate estimation, especially when using waveform lidar, since backscattered signals are likely distorted by topographic conditions within the footprint. Based on extracted waveform parameters, we explore how well a physical slope correction approach performs across different footprint sizes and study sites. The data are derived from airborne (Laser Vegetation Imaging Sensor; LVIS) and spaceborne (Geoscience Laser Altimeter System; GLAS) lidar campaigns. Comparisons against field measurements show that LVIS data can satisfactorily provide a proxy for maximum forest canopy heights (n = 705, RMSE = 4.99 m, and R² = 0.78), and the simple slope correction grants slight accuracy advancement in the LVIS canopy height retrieval (RMSE of 0.39 m improved). In the same vein of the LVIS with relatively smaller footprint size (∼20 m), substantial progress resulted from the physically-based correction for the GLAS (footprint size = ∼50 m). When compared against reference LVIS data, RMSE and R² for the GLAS metrics (n = 527) are improved from 12.74–7.83 m and from 0.54–0.63, respectively. RMSE of 5.32 m and R² of 0.80 are finally achieved without 38 outliers (n = 489). From this study, we found that both LVIS and GLAS lidar campaigns could be benefited from the physical correction approach, and the magnitude of accuracy improvement was determined by footprint size and terrain slope.

【 授权许可】

CC BY   
© 2014 by the authors; licensee MDPI, Basel, Switzerland