tdholodok.ru
Log In

Forest in situ observations using unmanned aerial vehicle as an

$ 11.50

4.9 (382) In stock

Background Lately, terrestrial point clouds have drawn attention as a new data source for in situ forest investigations. So far, terrestrial laser scanning (TLS) has the highest data quality among all terrestrial point cloud data in terms of geometric accuracy and level of detail (IEEE Transact Geosci Remote Sens 53: 5117–5132, 2015). The TLS point clouds processed by automated algorithms can provide certain individual tree parameters at close to required accuracy in practical applications. However, all terrestrial point clouds face a general challenge, which is the occlusions of upper tree crowns. An emerging technology called unmanned-aerial-vehicle (UAV) - borne laser scanning (ULS) potentially combines the strengths of above and under canopy surveys. Results The performance of ULS are evaluated in 22 sample plots of various forest stand conditions in a boreal forest. The forest parameter estimates are benchmarked through a comparison with state-of-the-art terrestrial mechanisms from both static terrestrial and mobile laser scanning. The results show that in easy forest stand conditions, the performance of ULS point cloud is comparable with the terrestrial solutions. Conclusions This study gives the first strict evaluation of ULS in situ observations in varied forest conditions. The study also acts as a benchmarking of available active remote sensing techniques for forest in situ mensuration. The results indicate that the current off-the-shelf ULS has an excellent tree height/tops measurement performance. Although the geometrical accuracy of the ULS data, especially at the stem parts, does not yet reach the level of other terrestrial point clouds, the unbeatable high mobility and fast data acquisition make the ULS a very attractive option in forest investigations.

Unmanned aerial vehicle - Wikipedia

Forest in situ observations using unmanned aerial vehicle as an alternative of terrestrial measurements, Forest Ecosystems

Frontiers Automatic instance segmentation of orchard canopy in unmanned aerial vehicle imagery using deep learning

Seamless integration of above- and under-canopy unmanned aerial

Seamless integration of above- and under-canopy unmanned aerial

Artificial intelligence-based software (AID-FOREST) for tree detection: A new framework for fast and accurate forest inventorying using LiDAR point clouds - ScienceDirect

Seamless integration of above- and under-canopy unmanned aerial

UNH Online Research Conference

Remote Sensing, Free Full-Text

Remote Sensing, Free Full-Text

Remote Sensing, Free Full-Text

Mean (left) and median (right) spectra of various tree species (only

Remote Sensing, Free Full-Text

Forests, Free Full-Text

Related products

The science of forest bathing: 5 ways it can boost health and lower stress : Life Kit : NPR

Middle Beach Lodge

Lake Forest Middle School

Medium forest vs dark forest vs green jasper vs tidewater teal : r

How Much Can Trees Fight Climate Change? Massively, but Not Alone