Land cover monitoring is a major task for remote sensing. Comparing to traditional methods for forests monitoring which mostly use orthoimages from satellite or aircraft, there are very few researches use forest 3D canopy structure to monitor the forest growth. UAV aerial can be a novel and feasible platform to provide high resolution and more timely images that can be used to generate high resolution forest 3D canopy. In spring, the small forest is supposed to experience rapid growth. In this research, we used a small UAV to monitor campus forest growth in spring at 2days interval. Each time 140 images were acquired and the ground surface dense point cloud was reconstructed at high precision. Color indexes ExG (Excess Green) was used to extract the green canopy point. The segmented point cloud was triangulated using greedy projection triangulation method into a mesh and its area was calculated. Forest canopy growth was analyzed at 3 level: forest level, selected group level and individual tree level. Logistic curve was used to fit the time series canopy growth. Strong correlation was found R2 = 0.8517 at forest level, R2=0.9652 at selected group level and R2 = 0.9606 at individual tree level. Moreover, high correlation was found between canopy by observing these results, we can conclude that the ground 3D model can act as a useful data type as orthography to monitor the forest growth. Moreover the UAV aerial remote sensing has advantages at monitoring forest in periods when the ground vegetation is growing and changing fast.

Laser ranging based on a single-photon avalanche diode (SPAD), offering single-photon level high sensitivity, has been widely adopted in light detection and ranging (lidar) systems for long-distance ranging and imaging applications. Count detection through multiple pulses is commonly used when considering the existence of dark counting and strong background counting during the daytime, which improves the signal-to-noise ratio but at the expense of low detection speed. Here, we report a novel coded-pulse-bunch-laser-based single-photon lidar system, which aims to improve the ranging speed greatly and to expand the unambiguous distance to several kilometers. The schematic principle and construction of the lidar system, as well as the encoding method, are introduced. The time-of-flight (TOF) ranging information is extracted through real-time correlation between the transmitted pulse-bunch patterns and the received echo signals in a field-programmable gate array (FPGA). A daytime ranging experiment is demonstrated on a non-cooperative mountain target that is 5.4 km away. The method will be of great potential in fast three-dimension (3D) single-photon lidar imaging application for its relatively high data refreshing rate and large unambiguous distance.

The operational space control (OSC) of multilink cable-driven hyper-redundant robots (MCDHRs) are required to perform tasks in many applications. As a new coupled active-passive (CAP) MCDHR system, due to the multiple couplings between the active cables, the passive cables, the joints, and the end-effector, the OSC becomes more and more complicated. However, there is currently no robust and effective control method to solve the OSC problem of such types MCDHRs. In this paper, an OSC framework of CAP-MCDHRs using a dynamics-based iterative-learning-control (ILC) method is proposed, considering multivariate optimization. First, the multi-coupling kinematics and the series-parallel coupling dynamics equation (i.e., cable-joint-end) of the CAP-MCDHR are derived. Then, a dynamics-based trajectory tracking framework was constructed. Moreover, an OSC accuracy evaluation model based on a high-precision laser tracker was also designed. The framework allows the tracking of operational space trajectories (OSTs) online with the feasible cables tension and the joint angle. It is also shown that the tracking performance can be improved through the ILC when the desired trajectory is repeatedly performed. Finally, a simulation and an experimental hardware system is built. The results show that the proposed control framework can be easily and effectively applied to the CAP-MCDHR used in real time.