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 and understory vegetation is essential to study forest carbon and water cycles. Measuring PAI of overstory and understory vegetation 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 understory vegetation is usually measured by the conventional method of subtracting PAIe of overstory vegetation from total PAIe. We find PAIe obtained using this strategy is underestimated by 25% to 85%. Thus, we propose an approach to estimate PAIe and PAI of both overstory and understory vegetation on sloped terrain by using single-station terrestrial laser scanner (TLS) data. Results are verified by comparing them with multi-station TLS data acquired coincidentally. Then we analyze the effects of horizontal range and slope correction on PAI estimated from single-station TLS data. The results show that the correlation between single-station and multi-station PAI (PAIe) is strong, with R ² of 0.88 (0.81) and 0.52 (0.75) ( p <0.01) for overstory and understory vegetation, respectively. We recommend imposing a horizontal 20 m-radius range for data acquired from single-station TLS for PAI estimations. The difference between PAI estimations with and without a slope correction can be neglected. These results demonstrate that single-station TLS data can serve as a means for PAI estimations of both overstory and understory vegetation, which should help facilitate large-scale estimation in the subtropical forests of China.