1. Compared to using ABA features alone, combining ABA and ITA features resulted in a higher R 2 (Figure 5a, e) and lower RMSE (Figure 5c, g) for both regions;features and the algorithms
2. Deep learning for forest inventory and planning: a critical review on the remote sensing approaches so far and prospects for further applications;H Alireza;Forestry,2022
3. Monitoring restored tropical forest diversity and structure through UAV-borne hyperspectral and lidar fusion;D R A D Almeida;Remote Sensing of Environment,2021
4. The use of waveform lidar to measure northern temperate mixed conifer and deciduous forest structure in New Hampshire;J Anderson;Remote Sensing of Environment,2006