Under the premise of sufficient lighting or illumination and with insignificant water flow disturbance, this study focuses on the flat-refractive imaging system, where a camera is facilitated in a housing device and acquires the images underwater, a typical configuration in underwater photogrammetry. The imaging path of flat-refractive imaging system involves multimedia environment, where both imaging and positioning are influenced by the refraction effect. Accurate determination of interior and exterior orientation, distortion parameters, and glass-related parameters such as glass thickness, the distance from the perspective center to the interface, the tilt of the glass interface, and refractive indices is essential to construct the correct imaging path and solve tasks related to object-to-image correspondence. In the object-to-image correspondence model of underwater photogrammetry proposed in this study, simulations and actual experiments were conducted to analyze the influence of parameter errors and intersection geometry on the positioning quality of object points, validating the feasibility and effectiveness of the model. The results provide a reference for object space positioning in underwater photogrammetry, enabling users to identify the errors of influential factors and select appropriate configurations based on task requirements.

The application of photogrammetry point clouds across various fields often faces challenges due to the massive data volume, which affects storage and computational efficiency. Simplifying point clouds while preserving geometric features has thus become a critical task. Existing methods largely rely on empirical rules, making them less adaptable to varying regional characteristics. This study improves upon a point cloud simplification method based on edge points, feature points, and non-feature points, incorporating an adaptive neighborhood size to preserve features. The approach begins with noise filtering, followed by using Principal Component Analysis (PCA) to derive curvature and entropy for constructing a topological structure that distinguishes between irregular and regular regions. After extracting edge points, the importance of feature points is assessed, and non-feature points are reduced to achieve simplification with feature retention. Experimental results show that the proposed method effectively preserves major geometric features across different scenarios. However, at high simplification rates, fine details may become blurred. In the future, performance could be further enhanced by implementing automated parameter setup.

This study analyzes monthly Moderate-resolution Imaging Spectroradiometer (MODIS)-Aqua sea surface chlorophyll-a (SChl-a) data and finds significantly high SChl-a concentrations along the northern coast of Luzon Island compared to its surrounding areas. In the Cagayan River estuary near the Luzon Strait, the average SChl-a concentration in the cold phase of the Pacific Decadal Oscillation (PDO) is up to 0.14 mg/m3 higher than that in the warm phase. In months with negative PDO index (cold phase), geostrophic current composites show the oligotrophic Kuroshio current weakens north of the northeastern tip of Luzon Island (approximately 18°N) and strengthens south. A significant negative correlation was found between the PDO index and cumulative precipitation within the Cagayan River basin, as measured by the Tropical Rainfall Measuring Mission (TRMM) during this period. SChl-a concentrations thrive in the Cagayan River estuary because precipitation, geostrophic currents, and local bathymetry create an ideal environment that retains nutrient-dense materials. During the negative phase of the PDO, the pattern of the geostrophic current prevents the nutrient-poor Kuroshio water from entering the South China Sea via the southern Luzon Strait and traps the SChl-a in this sea area. This study elucidates the complex relationship between terrestrial precipitation and oceanic currents in regulating SChl-a concentrations in this important ecosystem under climatic variability.

This research utilizes Feng Chia University as a demonstration site to investigate the spatial distribution and spatiotemporal behavioral patterns of campus users by analyzing data from the university's wireless network. Two primary variables, namely "user count" and "duration of stay," are employed alongside cluster analysis to define and categorize spatial characteristic patterns, facilitating an analysis of two distinct scenarios. The findings reveal that " flow and communication spaces" are predominantly situated in accessible locations on lower floors, whereas "research and laboratory spaces" exhibit sensitivity to external conditions, resulting in distinct spatial characteristics. Consequently, the study recommends that " flow and communication spaces " adopt a more open spatial design and incorporate relevant facilities to enhance overall utilization efficiency. In contrast, it is suggested that " research and laboratory spaces " should be strategically located in areas with higher privacy and seclusion. Ultimately, this research aims to support the establishment of a data-driven, intelligent, service-oriented campus environment.