TY - JOUR
T1 - Canopy leaf water content estimated using terrestrial LiDAR
AU - Zhu, Xi
AU - Wang, Tiejun
AU - Skidmore, Andrew K.
AU - Darvishzadeh, Roshanak
AU - Niemann, K. Olaf
AU - Liu, Jing
PY - 2017/1/15
Y1 - 2017/1/15
N2 - Leaf water content (LWC) within a plant canopy plays an important role in light penetration and scattering, thus affecting reflectance simulation with radiative transfer models. It is also of key importance for the distribution of other plant biochemical parameters, fire propagation simulation and habitat suitability evaluation. Although passive remote sensing techniques have been widely applied to estimate LWC, they are unable to retrieve the LWC vertical distribution within a canopy. In this paper we investigated the applicability of the full-waveform terrestrial laser scanning data (TLS) to estimate the LWC vertical distribution within the canopy of individual plants. A modified skewed Gaussian function that accommodates the nonlinear nature of the system was proposed to perform a decomposition on the full-waveform data. The amplitude, the backscatter cross-section, and the backscatter coefficient were assessed to estimate LWC, respectively. Our results showed that the backscatter coefficient had the strongest correlation with LWC (R2 = 0.66) for four plant species after an incidence angle correction. Good agreements were achieved between the predicted vertical profile of LWC and the measured vertical profile of LWC with a mean RMSE (root mean square error) value of 0.001 g/cm2 and a mean MAPE (mean absolute percent error) value of 4.46%. However, the performance of LWC vertical profile estimation varied across species, suggesting the influence of leaf structure other than LWC on waveform features, which should be considered in future studies. Nevertheless, our study successfully demonstrated the feasibility of retrieving LWC vertical distribution within plant canopy from a full-waveform terrestrial laser scanner.
AB - Leaf water content (LWC) within a plant canopy plays an important role in light penetration and scattering, thus affecting reflectance simulation with radiative transfer models. It is also of key importance for the distribution of other plant biochemical parameters, fire propagation simulation and habitat suitability evaluation. Although passive remote sensing techniques have been widely applied to estimate LWC, they are unable to retrieve the LWC vertical distribution within a canopy. In this paper we investigated the applicability of the full-waveform terrestrial laser scanning data (TLS) to estimate the LWC vertical distribution within the canopy of individual plants. A modified skewed Gaussian function that accommodates the nonlinear nature of the system was proposed to perform a decomposition on the full-waveform data. The amplitude, the backscatter cross-section, and the backscatter coefficient were assessed to estimate LWC, respectively. Our results showed that the backscatter coefficient had the strongest correlation with LWC (R2 = 0.66) for four plant species after an incidence angle correction. Good agreements were achieved between the predicted vertical profile of LWC and the measured vertical profile of LWC with a mean RMSE (root mean square error) value of 0.001 g/cm2 and a mean MAPE (mean absolute percent error) value of 4.46%. However, the performance of LWC vertical profile estimation varied across species, suggesting the influence of leaf structure other than LWC on waveform features, which should be considered in future studies. Nevertheless, our study successfully demonstrated the feasibility of retrieving LWC vertical distribution within plant canopy from a full-waveform terrestrial laser scanner.
KW - Leaf water content
KW - Vertical distribution
KW - Full-waveform
KW - Terrestrial laser scanner
KW - Backscattering coefficient
UR - http://www.scopus.com/inward/record.url?scp=84989825011&partnerID=8YFLogxK
U2 - 10.1016/j.agrformet.2016.08.016
DO - 10.1016/j.agrformet.2016.08.016
M3 - Article
AN - SCOPUS:84989825011
VL - 232
SP - 152
EP - 162
JO - Agricultural and Forest Meteorology
JF - Agricultural and Forest Meteorology
SN - 0168-1923
ER -