@inproceedings{02891a19165747d3a4165712d0ef8629,
title = "Retrieval of the Forest Leaf Area Index Based on the Laser Penetration Ratio from the GLAS Waveform Lidar Data",
abstract = "Leaf area index (LAI) is an important structure parameter to illuminate the fractions of solar radiation absorbed, transmitted and reflected by the plant canopy, and also a useful reference for ecological and meteorological modeling. The GLAS full-waveform Lidar data of ICESat satellite are easily available and global coverage, which can also provide detailed forest canopy structure information in the GLAS footprint. In this study, we show a LAI estimation method from the GLAS waveform Lidar data at footprint level. Firstly, Gaussian decomposition method is used to process the raw GLAS waveform data to identify ground echo energy and canopy echo energy. In addition, the optical height threshold (HT) to separate the canopy and ground in the GLAS waveform has been discussed, and the result show that 3 m is the optical HT in our study area. Secondly, a reflectance correction method is used to calculate the laser penetration ratio (PC) of forest covered GLAS footprints based on the ground echo energy and canopy echo energy. Thirdly, the relationship between the between the field-measured LAIs and PC is constructed based on the Beer-Lambert law. The determination coefficient (R2) is 0.69 and the root mean square error (RMSE) is 0.64. The performance of the GLAS-derived LAIs is also evaluated using the 20 field-measured LAIs. The result indicates that the GLAS-derived LAIs have a high accordance with the field measurements (R2=0.67, RMSE=0.52). The result suggests that the GLAS waveform data can be used to retrieval LAI for various ecological applications.",
keywords = "Beer-Lambert law, GLAS, LAI, gap fraction, waveform Lidar",
author = "Lei Cui and Jing Guo and Ziti Jiao and Mei Sun and Yadong Dong and Xiaoning Zhang and Siyang Yin and Yaxuan Chang and Anxing DIng and Rui Xie",
note = "Publisher Copyright: {\textcopyright} 2019 IEEE.; 39th IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 ; Conference date: 28-07-2019 Through 02-08-2019",
year = "2019",
month = jul,
doi = "10.1109/IGARSS.2019.8898057",
language = "English",
series = "International Geoscience and Remote Sensing Symposium (IGARSS)",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "8972--8975",
booktitle = "2019 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2019 - Proceedings",
address = "United States",
}