Dear all
Firstly, what a fantastic group! I love following the discussions on this site and am a true believer in the power of the crowd so am hoping someone might have the expertise to help answer my question!
I am hoping to get some advice about using LiDAR scanners for forest surveys in Amazonia. I have seen a lot of research that uses LiDAR to build point clouds from which tree measures (DBH, heights etc) can be taken for forest surveys but most of these use super expensive devices and for someone without experience using this tech it is difficult to tell what options are best so I thought I'd ask whether anyone here could recommend LiDAR devices that are a) affordable (<$1000), b) good for tree measures and that are c) easy to use. It'd also be helpful to get peoples' opinions on the use of UAV vs terrestrial scanners and whether the former would even work in dense tropical forest? One specific example I come across was the Livox MID series that are available for only $5-900 from DJI. However, they were developed for industrial use so I don't know if they would be used for forest surveys but am wondering if this might be a suitable option?
Well, I hope someone will be able to help, there must suerly be someone else who has used LiDAR so I look forward to any responses.
Regards,
Jeremy
6 April 2023 6:21pm
Hi Jeremy,
With a quick search I've found the paper linked below. It looks like equipments such as Livox MID are sufficient for plot-level analyses, but not for individual trees. Also, it has performed worse in dense canopies and broadleaf forest, thus I believe we won't have a technology capable of doing what you aim for this amount of money (< $1000) in a few years from now.
I hope someone give us an alternative, though. :D
Best,
Development and Performance Evaluation of a Very Low-Cost UAV-Lidar System for Forestry Applications
Accurate and repeated forest inventory data are critical to understand forest ecosystem processes and manage forest resources. In recent years, unmanned aerial vehicle (UAV)-borne light detection and ranging (lidar) systems have demonstrated effectiveness at deriving forest inventory attributes. However, their high cost has largely prevented them from being used in large-scale forest applications. Here, we developed a very low-cost UAV lidar system that integrates a recently emerged DJI Livox MID40 laser scanner (~$600 USD) and evaluated its capability in estimating both individual tree-level (i.e., tree height) and plot-level forest inventory attributes (i.e., canopy cover, gap fraction, and leaf area index (LAI)). Moreover, a comprehensive comparison was conducted between the developed DJI Livox system and four other UAV lidar systems equipped with high-end laser scanners (i.e., RIEGL VUX-1 UAV, RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE). Using these instruments, we surveyed a coniferous forest site and a broadleaved forest site, with tree densities ranging from 500 trees/ha to 3000 trees/ha, with 52 UAV flights at different flying height and speed combinations. The developed DJI Livox MID40 system effectively captured the upper canopy structure and terrain surface information at both forest sites. The estimated individual tree height was highly correlated with field measurements (coniferous site: R2 = 0.96, root mean squared error/RMSE = 0.59 m; broadleaved site: R2 = 0.70, RMSE = 1.63 m). The plot-level estimates of canopy cover, gap fraction, and LAI corresponded well with those derived from the high-end RIEGL VUX-1 UAV system but tended to have systematic biases in areas with medium to high canopy densities. Overall, the DJI Livox MID40 system performed comparably to the RIEGL miniVUX-1 UAV, HESAI Pandar40, and Velodyne Puck LITE systems in the coniferous site and to the Velodyne Puck LITE system in the broadleaved forest. Despite its apparent weaknesses of limited sensitivity to low-intensity returns and narrow field of view, we believe that the very low-cost system developed by this study can largely broaden the potential use of UAV lidar in forest inventory applications. This study also provides guidance for the selection of the appropriate UAV lidar system and flight specifications for forest research and management.
MDPI
Eduardo Zanette