LiDAR footprint, defined as the illumination area of LiDAR sensor on the ground, is the fundamental unit that the sensor collects information from. The design of footprint size crucially influences the acquired LiDAR signals. For large-footprint full-waveform LiDAR, a well-designed footprint size is indispensable to acquire accurate and complete vertical profiles of scene targets. The methods that design the footprint size are increasingly needed to satisfy various application requirements. In this study, an analytical method to designing the footprint size is proposed for forest and topography applications. It is established based on a mixture Gaussian model and the designed footprint size ensures the signals of vegetation and ground can be completely extracted. Experiment results with our method show that the footprint size is preferably in the range of 10.6–25.0 m for forest application, while it is less than 32.3 m for topography application. The intersection of the two sets satisfies both applications. Furthermore, a series of sensibility studies were performed to analyze the influence of multiple key parameters to the optimal footprint size, including the scene characteristics, instrumental configurations, and application requirements. This study provides a theoretical basis for the design of future large-footprint full-waveform laser altimeters.

Reaction pathways, solvent effects and energy barriers have been investigated for the dehydration processes of aquated Al(OH)₂ ⁺ species in aqueous solution by density functional calculations using a supermolecule model. The dehydration processes from Al(H₂O)₄(OH)₂ ⁺ to Al(H₂O)₂(OH)₂ ⁺ involve the water exchange on cis-Al(H₂O)₄(OH)₂ ⁺ and dehydration of the following intermediate pentacoordinate Al(H₂O)₃(OH)₂ ⁺. The calculated results indicate that cis-Al(H₂O)₄(OH)₂ ⁺ exchanges water in a dissociative way with an activation energy of 27.7 kJ mol⁻¹. Loss of coordinated water from hexacoordinate and pentacoordinate Al(OH)₂ ⁺ is unfavourable by 22.1 and 6.6 kJ mol⁻¹, respectively, which supports the presence of the stable hexacoordinate Al(H₂O)₄(OH)₂ ⁺ in aqueous solution. Our results also indicate that both the explicit water molecules and bulk water molecules have great influences on the energy barriers, and they can not be neglected.

Radiative transfer models (RTMs) are often used to retrieve biophysical parameters from earth observation data. RTMs with multi-temporal and realistic forest representations enable radiative transfer (RT) modeling for real-world dynamic processes. To achieve more realistic RT modeling for dynamic forest processes, this study presents the 3D-explicit reconstruction of a typical temperate deciduous forest in 2015 and 2022. We demonstrate for the first time the potential use of bitemporal 3D-explicit RT modeling from terrestrial laser scanning on the forward modeling and quantitative interpretation of: (1) remote sensing (RS) observations of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (FAPAR), and canopy light extinction, and (2) the impact of canopy gap dynamics on light availability of explicit locations. Results showed that, compared to the 2015 scene, the hemispherical-directional reflectance factor (HDRF) of the 2022 forest scene relatively decreased by 3.8% and the leaf FAPAR relatively increased by 5.4%. At explicit locations where canopy gaps significantly changed between the 2015 scene and the 2022 scene, only under diffuse light did the branch damage and closing gap significantly impact ground light availability. This study provides the first bitemporal RT comparison based on the 3D RT modeling, which uses one of the most realistic bitemporal forest scenes as the structural input. This bitemporal 3D-explicit forest RT modeling allows spatially explicit modeling over time under fully controlled experimental conditions in one of the most realistic virtual environments, thus delivering a powerful tool for studying canopy light regimes as impacted by dynamics in forest structure and developing RS inversion schemes on forest structural changes.