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Challenges have been observed in the traditional circumferential-scanning LiDAR underwater to balance between the detection range and the sealing performance. To tackle these challenges, a new scanning unit is presented in this paper, employing a pyramidal-shaped reflector for enhanced performance. Furthermore, an innovative magneto–electric detection module comprising Hall switches and magnetic rings is introduced. It can facilitate the accurate identification of the reflector’s edge, thereby enhancing the precision of the target-orientation detection. A rapid target orientation coding method based on split-frequency clocks is proposed on FPGAs. It can output the target’s initial and termination orientation codes immediately after capturing it, exhibiting a significantly low output delay of 20 ns and a high detection resolution of 15°. Finally, a prototype is fabricated to validate the design in this paper. The experimental results demonstrate that the scanning unit enables reliable scanning and orientation recognition of the target. In addition, it is trustworthy in receiving echo signals when the laser passes through glass and then an aqueous medium.

As a key role in hindering the large-scale application of fuel cells, oxygen reduction reaction has always been a hot issue and nodus. Aiming to explore state-of-art electrocatalysts, this paper reviews the latest development of nonmetallic catalysts in oxygen reduction reactions, including single atoms doped with carbon materials such as N, B, P or S and multi-doped carbon materials. Afterward, the remaining challenges and research directions of carbon-based nonmetallic catalysts are prospected.

Park green space is an important part of the green infrastructure in a city, and urban park space accessibility is an important indicator for measuring the city’s comprehensive strength, living environment, and resident happiness, which greatly affects the sustainable development and construction of the city. The spatial syntax method can discuss the accessibility of urban parks from the perspective of topology, which inherits the objective stability of the topological relationship. There are few research studies on the accessibility of urban parks. Therefore, with the support of space syntax theory and the spatial statistics method, this paper combined the data of park green space and road network to complete the accessibility evaluation of urban parks in the Changsha City urban area. This paper evaluates the accessibility of urban parks in the study area from four aspects, namely global accessibility, perceptual accessibility, local accessibility, and psychological accessibility, by using five quantitative indexes of space syntax, namely connectivity, depth, integration, selection, and synergy. The conclusions are as follows: The spatial layout area of the park is roughly consistent with the areas that have good global and local accessibility of the road network, and the global accessibility and local accessibility of the park in the study area are relatively high. The global spatial structure can be better perceived by the local space at a radius scale greater than or equal to 3000 m, and the perceptual accessibility of the park is high. Most of the urban parks in the Changsha urban area are located in sections with high space efficiency. The park space penetration is good, and nearly 70% of the parks have high psychological accessibility. Based on the overall spatial layout of urban parks, the space syntax method quantitatively and comprehensively evaluates the accessibility of urban parks from the perspective of topology. The conclusion is reliable and has important application value in the evaluation of park accessibility. It can be used as an important supplement to improve the evaluation model of accessibility.

Exploring the heterogeneous characteristics of the urban expansion process is essential for understanding the dynamics of the urban spatial structure. Many studies focused on depicting the spatio-temporal characteristics based on urban expansion patches. However, measuring heterogeneous characteristics of urban expansion from agglomeration areas comprising the expanded urban construction land patches have not been adequately explored. This study presents a novel approach and two improved indices for characterizing the heterogeneity of urban spatial agglomeration areas during urban expansion. Firstly, we proposed a Gaussian mixture model considering multiple constrains and density-based spatial clustering of applications with noise (DBSCAN) integration method to identify and extract the urban agglomeration areas automatically. Secondly, the gradient analysis and the compact index using the inverse “S” function are introduced to explore the spatio-temporal characteristics from a macrocosmic perspective. Finally, the compactness index (NCI) and normalized dispersion index (NDIS) are improved based on agglomeration area data. The microcosmic heterogeneous characteristics are measured by these two improved indices and the positional offset characteristics indices (POCIS). The method was implemented in the urban area of Changsha, Hunan Province, China in 2005, 2010, and 2015. The results show that (1) compared to that in the Changsha City Master Plan (2003–2020), the recognition rate was higher in the agglomeration areas than others. (2) The overall expansion trend in Changsha transitioned toward decentralization, making Changsha a polycentric city. (3) The agglomeration of urban expansion in the east-west direction became compact; that in the north-south direction became looser; most clusters expanded to the west and a new sub-center would appear. The proposed method can effectively characterize their heterogeneity, which can provide valuable references for urban planning and policymaking.

GPS trajectory and remote sensing data are crucial for updating urban road networks because they contain critical spatial and temporal information. Existing road network updating methods, whether trajectory-based (TB) or image-based (IB), do not integrate the characteristics of both types of data. This paper proposed and implemented an incremental update method for rapid road network checking and updating. A composite update framework for road networks is established, which integrates trajectory data and UAV remote sensing imagery. The research proposed utilizing connectivity between adjacent matched points to solve the problem of updating problematic road segments in networks based on the features of the Hidden Markov Model (HMM) map-matching method in identifying new road segments. Deep learning is used to update the local road network in conjunction with the flexible and high-precision characteristics of UAV remote sensing. Additionally, the proposed method is evaluated against two baseline methods through extensive experiments based on real-world trajectories and UAV remote sensing imagery. The results show that our method has higher extraction accuracy than the TB method and faster updates than the IB method.

The interface problem exists widely in building. Joints are interfaces of rock mass structures. To further study the influence of morphological characteristics on the shear mechanical properties of sawtooth joints, this paper prepared rock-like materials based on the similarity principle and carried out direct shear tests of sawtooth joints. The results showed that: (1) the peak shear displacement of joints first increases and then decreases with increasing normal stress, but the normal trend of stress during turning is different under different sawtooth angles. When the sawtooth angle of the joints is small, the decrease in shear stress between shear strength and residual shear strength is not obvious, and the rate of decrease is also small. (2) The shear strength of joints is positively correlated with normal stress. Using the Mohr–Coulomb criterion to analyze the shear strength of joints, it was found that the cohesion c and internal friction angle α of joints increased nonlinearly with increasing sawtooth angle, but their increasing trends were different. By introducing the function relation between cohesion, internal friction angle, and sawtooth angle into the classical shear strength equation, an empirical equation for the shear strength of joints was established in consideration of sawtooth angle. (3) There are two modes of shear failure for serrated joints: the “saw-toothed sliding gnawing failure mechanism” (SSG) and the “tensile fracture mechanism” (TFM). In the SSG, the shear failure mode of joints evolves in a slipping–gnawing–complete gnawing mechanism with increasing sawtooth angle and normal stress. The TFM mainly occurs at high sawtooth angles. This study provides a theoretical reference for the prediction and prevention of geological disasters.

With the rapid development of LBSs (location-based services) in recent years, researchers have increasingly taken an interest in trying to make travel routes more practicable and individualized. Despite the fact that many studies have been conducted on routes using LBS data, the specific routes are deficient in dynamic scalability and the correlations between environmental constraints and personal choices have not been investigated. This paper proposes an improved HMM-based (hidden Markov model) method for planning personalized routes with crowd sourcing spatiotemporal data. It tries to integrate the dynamic public preferences, the individual interests and the physical road network space in the same spatiotemporal framework, ensuring that reasonable routes will be generated. A novel dual-layer mapping structure has been proposed to bridge the gap from brief individual preferences to specific entries of POIs (points-of-interest) inside realistic road networks. A case study on Changsha city has proven that the proposed method can not only flexibly plan people’s travel routes under different spatiotemporal backgrounds but also is close to people’s natural selection by the perception of the group.

Accurately quantifying water inundation dynamics in terms of both spatial distributions and temporal variability is essential for water resources management. Currently, the water map is usually derived from synthetic aperture radar (SAR) data with the support of auxiliary datasets, using thresholding methods and followed by morphological operations to further refine the results. However, auxiliary datasets may lose efficacy on large plain areas, whilst the parameters of morphological operations are hard to be decided in different situations. Here, a heuristic and automatic water extraction (HAWE) method is proposed to extract the water map from Sentinel-1 SAR data. In the HAWE, we integrate tile-based thresholding and the active contour model, in which the former provides a convincing initial water map used as a heuristic input, and the latter refines the initial map by using image gradient information. The proposed approach was tested on the Dongting Lake plain (China) by comparing the extracted water map with the reference data derived from the Sentinel-2 dataset. For the two selected test sites, the overall accuracy of water classification is between 94.90% and 97.21% whilst the Kappa coefficient is within the range of 0.89 and 0.94. For the entire study area, the overall accuracy is between 94.32% and 96.7% and the Kappa coefficient ranges from 0.80 to 0.90. The results show that the proposed method is capable of extracting water inundations with satisfying accuracy.

To organize trajectory data is a challenging issue for both studies on spatial databases and spatial data mining in the last decade, especially where there is semantic information involved. The high-level semantic features of trajectory data exploit human movement interrelated with geographic context, which is becoming increasingly important in representing and analyzing actual information contained in movements and further processing. This paper argues for a novel semantic trajectory model named TOST. It considers both semantic and geographic information of trajectory data happens along network infrastructure simultaneously. In TOST, a flexible intersection-based semantic representation is designed to express movement typically constrained by urban road networks by combining sets of local semantic details along the time axis. A relational schema based on this model was instantiated against real datasets, which illustrated the effectivity of our proposed model.