Search Results (133)

Buildings are a significant component of urban space and are essential to smart cities, catastrophe monitoring, and land use planning. However, precisely extracting building polygons from remote sensing images remains difficult because of the variety of building designs and intricate backgrounds. This paper proposes an end-to-end polygon dynamic adjustment algorithm (PDAA) to improve the accuracy and geometric consistency of building contour extraction by dynamically generating and optimizing polygon vertices. The method first locates building instances through the region of interest (RoI) to generate initial polygons, and then uses four core modules for collaborative optimization: (1) the feature enhancement module captures local detail features to improve the robustness of vertex positioning; (2) the contour vertex tuning module fine-tunes vertex coordinates through displacement prediction to enhance geometric accuracy; (3) the learnable redundant vertex removal module screens key vertices based on a classification mechanism to eliminate redundancy; and (4) the missing vertex completion module iteratively restores missed vertices to ensure the integrity of complex contours. PDAA dynamically adjusts the number of vertices to adapt to the geometric characteristics of different buildings, while simplifying the prediction process and reducing computational complexity. Experiments on public datasets such as WHU, Vaihingen, and Inria show that PDAA significantly outperforms existing methods in terms of average precision (AP) and polygon similarity (PolySim). It is at least 2% higher than existing methods in terms of average precision (AP), and the generated polygonal contours are closer to the real building geometry. Values of 75.4% AP and 84.9% PolySim were achieved on the WHU dataset, effectively solving the problems of redundant vertices and contour smoothing, and providing high-precision building vector data support for scenarios such as smart cities and emergency response. Full article

3D (three-dimensional) property volume is an important data carrier for 3D land administration by using 3D cadastral technology, which can be used to express the legal space (property rights) scope matching with physical entities such as buildings and land. A 3D property volume is represented by a dense set of 3D coordinate points arranged in a predefined order and is displayed alongside the parcel map for reference and utilization by readers. To store a 3D property volume in the database, it is essential to record the connectivity relationships among the original 3D coordinate points, the associations between points and lines for representing boundary lines, and the relationships between lines for defining surfaces. Only by preserving the data structure that represents the relationships among points, lines, and surfaces can the 3D property volume in a parcel map be fully reconstructed. This approach inevitably results in the database storage volume significantly exceeding the original size of the point set, thereby causing storage redundancy. Consequently, this paper introduces a reversible 3D property volume compression coding method (called 3DPV-CC) to address this issue. By analyzing the distribution characteristics of the coordinate points of the 3D property volume, a specific rule for sorting the coordinate points is designed, enabling the database to have the ability of data storage and recovery by merely storing a reordered point set. The experimental results show that the 3DPV-CC method has excellent support capabilities for 3D property volumes of the vertical and slopped types, and can compress and restore the coordinate point set of the 3D property volume for drawing 3D parcel maps. The compression capacity of our method in the test is between 23.66% and 38.42%, higher than the general data compression methods (ZIP/7Z/RAR: 8.37–10.32%). By means of this method, land or real estate administrators from government departments can store 3D property volume data at a lower cost. This is conducive to enhancing the informatization level of land management. Full article

The automation in image acquisition and processing using UAV drones has the potential to acquire terrain data that can be utilized for the accurate production of 2D and 3D digital data. In this study, the DJI Phantom 4 drone was employed for large-scale topographical mapping, and based on the photogrammetric Structure-from-Motion (SfM) algorithm, drone-derived point clouds were used to generate the terrain DSM, DEM, contours, and the orthomosaic from which the topographical map features were digitized. An evaluation of the horizontal (X, Y) and vertical (Z) coordinates of the UAV drone points and the RTK-GNSS survey data showed that the Z-coordinates had the highest MAE(_X,Y,Z), RMSE_(X,Y,Z) and Accuracy_(X,Y,Z) errors. An integrated georeferencing of the UAV drone imagery using the mobile RTK-GNSS base station improved the 2D and 3D positional accuracies with an average 2D (X, Y) accuracy of <2 mm and height accuracy of −2.324 mm, with an overall 3D accuracy of −4.022 mm. Geometrically, the average difference in the perimeter and areas of the features from the RTK-GNSS and UAV drone topographical maps were −0.26% and −0.23%, respectively. The results achieved the recommended positional accuracy standards for the production of digital geospatial data, demonstrating the cost-effectiveness of low-cost UAV drones for large-scale topographical mapping. Full article

This paper addresses inherent limitations in unmanned aerial vehicle (UAV) undercarriages hindering vertical takeoff and landing (VTOL) capabilities on uneven slopes and obstacles. Robotic landing gear (RLG) designs have been proposed to address these limitations; however, existing designs are typically limited to ground slopes of 6–15°, beyond which rollover would happen. Moreover, articulated RLG concepts come with added complexity and weight penalties due to multiple drivetrain components. Previous research has highlighted that even a minor 3-degree slope change can increase the dynamic rollover risks by 40%. Therefore, the design optimization of robotic landing gear for enhanced VTOL capabilities requires a multidisciplinary framework that integrates static analysis, dynamic simulation, and control strategies for operations on complex terrain. This paper presents a novel, hybrid, compliant, belt-driven, three-legged RLG system, supported by a multidisciplinary design optimization (MDO) methodology, aimed at achieving enhanced VTOL capabilities on uneven surfaces and moving platforms like ship decks. The proposed system design utilizes compliant mechanisms featuring a series of three-flexure hinges (3SFH), to reduce the number of articulated drivetrain components and actuators. This results in a lower system weight, improved energy efficiency, and enhanced durability, compared to earlier fully actuated, articulated, four-legged, two-jointed designs. Additionally, the compliant belt-driven actuation mitigates issues such as backlash, wear, and high maintenance, while enabling smoother torque transfer and improved vibration damping relative to earlier three-legged cable-driven four-bar link RLG systems. The use of lightweight yet strong materials—aluminum and titanium—enables the legs to bend 19 and 26.57°, respectively, without failure. An animated simulation of full-contact landing tests, performed using a proportional-derivative (PD) controller and ship deck motion input, validate the performance of the design. Simulations are performed for a VTOL UAV, with two flexible legs made of aluminum, incorporating circular flexure hinges, and a passive third one positioned at the tail. The simulation results confirm stable landings with a 2 s settling time and only 2.29° of overshoot, well within the FAA-recommended maximum roll angle of 2.9°. Compared to the single-revolute (1R) model, the implementation of the optimal 3R Pseudo-Rigid-Body Model (PRBM) further improves accuracy by achieving a maximum tip deflection error of only 1.2%. It is anticipated that the proposed hybrid design would also offer improved durability and ease of maintenance, thereby enhancing functionality and safety in comparison with existing robotic landing gear systems. Full article

Localization is the foundation and core of autonomous driving. Current visual localization methods rely heavily on high-definition maps. However, high-definition maps are not only costly but also have poor real-time performance. In autonomous driving, place recognition is equally crucial and of great significance. Existing place recognition methods are deficient in local feature extraction and position and orientation errors can occur during the matching process. To address these limitations, this paper presents a robust multi-dimensional feature fusion framework for place recognition. Unlike existing methods such as OrienterNet, which homogenously process images and maps at the underlying feature level while neglecting modal disparities, our framework—applied to existing 2D maps—introduces a heterogeneous structural-semantic approach inspired by OrienterNet. It employs structured Stixel features (containing positional information) to capture image geometry, while representing the OSM environment through polar coordinate-based building distributions. Dedicated encoders are designed to adapt to each modality. Additionally, global relational features are generated by computing distances and angles between the current position and building pixels in the map, providing the system with detailed spatial relationship information. Subsequently, individual Stixel features are rotationally matched with global relations to achieve feature matching at diverse angles. During the BEV map matching process in OrienterNet, visual localization relies primarily on horizontal image information. In contrast, the novel method proposed herein performs matching based on vertical image information while fusing horizontal cues to complete place recognition. Extensive experimental results demonstrate that the proposed method significantly outperforms the mentioned state-of-the-art approaches in localization accuracy, effectively resolving the existing limitations. Full article

This study focuses on the systematic conservation of historical architectural heritage in Heilongjiang Province, particularly addressing the challenges of point-based protection and spatial fragmentation. It explores the construction of a connected and conductive heritage corridor network, using historical building clusters across the province as empirical cases. A comprehensive analytical framework is established by integrating the nearest neighbor index, kernel density estimation, minimum cumulative resistance (MCR) model, entropy weighting, circuit theory, and network structure metrics. Kernel density analysis reveals a distinct spatial aggregation pattern, characterized by “one core, multiple zones.” Seven resistance factors—including elevation, slope, land use, road networks, and service accessibility—are constructed, with weights assigned through an entropy-based method to generate an integrated resistance surface and suitability map. Circuit theory is employed to simulate cultural “current” flows, identifying 401 potential corridors at the provincial, municipal, and district levels. A hierarchical station system is further developed based on current density, forming a coordinated structure of primary trunks, secondary branches, and complementary nodes. The corridor network’s connectivity is evaluated using graph-theoretic indices (α, β, and γ), which indicate high levels of closure, structural complexity, and accessibility. The results yield the following key findings: (1) Historical architectural resources in Heilongjiang demonstrate significant coupling with the Chinese Eastern Railway and multi-ethnic cultural corridors, forming a “one horizontal, three vertical” spatial configuration. The horizontal axis (Qiqihar–Harbin–Mudanjiang) aligns with the core cultural route of the railway, while the three vertical axes (Qiqihar–Heihe, Harbin–Heihe, and Mudanjiang–Luobei) correspond to ethnic cultural pathways. This forms a framework of “railway as backbone, ethnicity as wings.” (2) Comparative analysis of corridor paths, railways, and highways reveals structural mismatches in certain regions, including absent high-speed connections along northern trunk lines, insufficient feeder lines in secondary corridors, sparse terminal links, and missing ecological stations near regional boundaries. To address these gaps, a three-tier transportation coordination strategy is recommended: it comprises provincial corridors linked to high-speed rail, municipal corridors aligned with conventional rail, and district corridors connected via highway systems. Key enhancement zones include Yichun–Heihe, Youyi–Hulin, and Hegang–Wuying, where targeted infrastructure upgrades and integrated station hubs are proposed. Based on these findings, this study proposes a comprehensive governance paradigm for heritage corridors that balances multi-level coordination (provincial–municipal–district) with ecological planning. A closed-loop strategy of “identification–analysis–optimization” is developed, featuring tiered collaboration, cultural–ecological synergy, and multi-agent dynamic evaluation. The framework provides a replicable methodology for integrated protection and spatial sustainability of historical architecture in Heilongjiang and other cold-region contexts. Full article

Climate governance operates across multiple administrative tiers, and enhancing the vertical coherence of policies has become a critical determinant of successful climate governance. This study employs data from 1578 counties in China from 2008 to 2022 to explore the synergistic effects between the Low Carbon City Policy (LCCP) and the Cadre Performance Evaluation System Transformation (CPEST). The study reveals that the CPEST has the potential to enhance the carbon reduction effects of the LCCP, yet it has not fully realized a synergistic effect. Further analysis indicates that although the timing arrangement is beneficial, it alone is insufficient to generate a synergistic effect. A synergistic impact only materializes when the objectives of the CPEST and LCCP are aligned, resulting in a carbon reduction effect that is approximately 1.5 times greater than the simple sum of their individual impacts. Mechanism analysis indicates that the combination of the LCCP and CPEST reduces carbon emissions primarily through four pathways: environmental investment, environmental penalties, green technology innovation, and upgrading of industrial structure. The effects of this combined approach are greater than those achieved through separate implementation. Heterogeneity analysis reveals that the combination of the LCCP and CPEST has a more pronounced effect in resource-based cities, old industrial bases, and regions with strong promotion incentives. The research findings provide both theoretical support and empirical evidence for enhancing vertical coordination in climate governance. Full article

Wind-induced vibrations in additional conductors on electrified railway catenary systems pose a risk to operational safety and long-term structural performance. This study investigates the dynamic response of these components under wind excitation through nonlinear finite element analysis. A wind speed spectrum model is developed using wind tunnel tests and field data, and the autoregressive method is used to generate realistic wind fields incorporating longitudinal, lateral, and vertical components. A detailed finite element model of the additional conductors and fittings was constructed using the Absolute Nodal Coordinate Formulation to account for large deformations. Time domain simulations with the Newmark-β method were conducted to analyze vibration responses. The results show that increased wind speeds lead to greater vibration amplitudes, and the stochastic nature of wind histories significantly affects vibration modes. Higher conductor tension effectively reduces vibrations, while longer spans increase flexibility and susceptibility to oscillation. The type of fitting also influences system stability; support-type fittings demonstrate lower stress fluctuations, reducing the likelihood of resonance. This study enhances understanding of wind-induced responses in additional conductor systems and informs strategies for vibration mitigation in high-speed railway infrastructure. Full article

We analyze a discrete-time random walk on the vertices of an unbounded two-dimensional L-lattice. We determine the probability generating function, and we prove the independence of the coordinates. In particular, we find a relation of each component with a one-dimensional biased random walk with time changing. Therefore, the transition probabilities and the main moments of the random walk can be obtained. The asymptotic behavior of the process is studied, both in the classical sense and involving the large deviations theory. We investigate first-passage-time problems of the random walk through certain straight lines, and we determine the related probabilities in closed form and other features of interest. Finally, we develop a simulation approach to study the first-exit problem of the process thought ellipses. Full article

Scanning forests with LiDAR is an efficient method for conducting forest resource surveys, including estimating tree diameter at breast height (DBH), canopy height, and segmenting individual trees. This study uses three-dimensional (3D) forest test data and point cloud data simulated by the Helios++ V1.3.0 software, and proposes a voxelized trunk extraction algorithm to determine the trunk location and the vertical structure of single tree trunks in forest areas. Firstly, the voxel-based shape recognition algorithm is used to extract the trunk structure of tree point clouds, then the random sample consensus (RANSAC) algorithm is used to solve the vertical structure connectivity problem of tree trunks generated by the above method, and the Alpha Shapes algorithm is selected among various point cloud surface reconstruction algorithms to reconstruct the surface of tree point clouds. Then, building on the tree surface model, a light projection scene is introduced to locate the tree trunk coordinates at different heights. Finally, the convex hull of the trunk bottom is solved by the Graham scanning method. Accuracy assessments show that the proposed single-tree extraction algorithm and the forest vertical structure recognition algorithm, when applied within the light projection scene, effectively delineate the regions where the vertical structure distribution of single tree trunks is inconsistent. Full article

This paper presents the results of investigations on the accuracy of contact point identification during coordinate measurement, which is crucial in the context of the Industry 4.0 concept. In particular, the effects of swivel length and probe declination angle during measurement were analyzed. In the experiments, deviations from the expected coordinates (0,0,0) of the contact point were analyzed for different rotational angles of the probing head. It was found that the recommended vertical positioning of the stylus at an angle of A = 0° might have introduced some insignificant errors. Increasing angle A up to 15° generated additional errors of negligible values in comparison with the measurement accuracy of the CMM. However, an increase in angle A up to 90° introduced additional errors as high as 10 μm. This contact point identification error will have a certain effect on the best fitting element and subsequent calculations and on the respective measurement results. Full article

This paper offers new insights into gravitational interactions within a general non-inertial reference frame. By utilizing symbolic tensor calculus, the study establishes a unified framework that connects time derivatives in non-inertial frames to those in inertial frames. The research introduces new first integrals of motion for a system of many particles in arbitrary non-inertial and barycentric rotating reference frames. These first integrals provide a kinematic and geometric visualization of motion in non-inertial frames. Additionally, a generalized potential energy function is presented for broader applicability. For the gravitational two-body problem, the paper delivers a closed-form, coordinate-free solution for the motion of each body relative to the original frame. Consequently, sufficient conditions for stability against collisions are established within the context of the two-body problem in a non-inertial reference frame. Furthermore, the paper examines the relative orbital motion of spacecraft, presenting a closed-form and coordinate-free solution in the local vertical local horizontal (LVLH) non-inertial frame, which is centered on the center of mass of the main spacecraft. Full article

Rapid urbanization worldwide poses significant challenges to biodiversity, as urban habitat fragmentation coexists with diverse landscape forms. Residential areas, a critical component of urban ecology, are essential for understanding the mechanisms that drive biodiversity conservation and the harmonious coexistence of humans and nature. Additionally, the gradient distribution of biodiversity remains a focal point in ecological research, aiding in the comprehension of fundamental species–environment interactions. In this study, we sampled 269 residential areas across fifteen counties and municipal districts on Hainan Island to investigate biodiversity alongside residential characteristics, as well as socio-economic and environmental variables. Utilizing the Generalized Linear Model (GLM), we analyzed the differences and commonalities of plant driving factors through horizontal and vertical two-dimensional gradient models with box plots, Principal Component Analysis (PCA), Principal Coordinate Analysis (PCoA), and path models to examine the existence, distribution, and nature of these gradients. Our findings indicate the following: different plant types are driven by distinct mechanisms; cultivated plants are primarily valued for ornamental purposes, whereas in rural areas, their edible value is emphasized. Urban residential plant diversity was primarily influenced by altitude and fundamentally affected by economic factors. Our analyses identified distinct differences in the driving factors influencing various plant types and established two primary gradients of plant diversity distribution within residential areas: a horizontal gradient influenced by housing prices and a vertical gradient corresponding to changes in elevation. Both gradient models were found to be outcomes of socio-economic factors, highlighting the significant role of economic development in shaping urban biodiversity. Full article

Month-long and seasonally persistent apparent tilts in atmospheric radar scatterers have been measured with a network of six windprofiler radars over periods of two or more years. The method used employs cross-correlations between vertical winds and horizontal winds measured using the radars. It is shown that large-scale apparent tilts that persisted for many weeks and months were not uncommon at many sites, with typical tilts varying from horizontal to ~3–4° from horizontal. The azimuthal and zenithal alignment of the tilts depend on local orography as well as local seasonal atmospheric conditions. It is demonstrated that these apparent tilts are not, in general, true large-scale phenomena, but rather are a manifestation of coordinated motions within turbulent and quasi-specular radar-scattering structures at scales between a few metres and tens of metres, with these structures themselves being defined by larger-scale and longer-term physical processes. Windshear combined with breaking gravity waves seems to be a particularly effective mechanism for producing these tilts, although other possibilities are also discussed. Implications for the interpretation of the nature of turbulent eddies, the accuracy of vertical wind measurements, and the nature of layering and scattering in the real atmosphere, are discussed. A method which allows for accurate measurements of the mean off-horizontal alignment of anisotropic scatterers and turbulent eddies is introduced. Full article

Tunable thermal expansion metamaterials exhibit superior shock absorption performance in the field of high-precision equipment, but the applications are currently restricted by the unclear quantitative relationship of temperature-induced deformation. Herein, this work leverages the virtual work principle and the deformation geometric relationship to establish a generic temperature-induced deformation control model for bi-materials by utilizing the key variable coverage ratio under the condition of no deformation in the vertical direction. The feasible region regarding flexibility for the internal serpentine unit and lattice structure with different coverage ratios is given. The combination of the finite element and experimental methods is adopted to examine temperature-induced deformation, which presents tunable thermal expansion performances associated with the coverage ratio and temperature. This work, based on the established deformation coordination relationship of dual-material temperature-sensitive metamaterials, achieves temperature-induced deformation control and provides a reference for structural design adaptable in various working conditions such as vibration isolation and vibration reduction in complex engineering such as aerospace and so on. By strategically designing the coverage of the two structures within the specified range to maintain equivalent flexibility, the ultimate deformation of the serpentine unit is reduced by one-half due to deformation induced by temperature variations. Full article