Quantifying the Plant Area Index of Overstory and Understory Vegetation on Sloped Terrain Using Single-Station Terrestrial Laser Scanner

Estimating forest plant area index (PAI) with the simultaneous separation of overstory vegetation (OV) and understory vegetation (UV) is essential to study forest carbon and water cycles. Measuring PAI of OV and UV using conventional field surveys within forests is challenging, particularly for subtropical regions of China, where terrain slope can exceed 10°. The effective PAI (PAIe) instead of PAI for UV is usually measured by the conventional method of subtracting PAIe of OV from total PAIe. We find PAIe obtained using this strategy is underestimated by 25%–85%. Thus, we propose an approach to estimate PAIe and PAI of both OV and UV on sloped terrain by using single-station (SS) terrestrial laser scanner (TLS) data. Results are verified by comparing them with multistation (MS) TLS data acquired coincidentally. Then we analyze the effects of horizontal range and slope correction on PAI estimated from SS TLS data. The results show that the correlation between SS and MS PAI (PAIe) is strong, with
$R^{2}$
of 0.88 (0.81) and 0.52 (0.75) (
${p}~\lt 0.01$
) for OV and UV, respectively. We recommend imposing a horizontal 20-m radius range for data acquired from SS TLS for PAI estimations. The difference between PAI estimations with and without a slope correction can be neglected. These results demonstrate that SS TLS data can serve as a means for PAI estimations of both OV and UV, which should help facilitate large-scale estimation in the subtropical forests of China.