Due to budget and sensor technology constraints, a single sensor cannot simultaneously provide observational images with both a high spatial and temporal resolution. To solve the above problem, the spatiotemporal fusion (STF) method was proposed and proved to be an indispensable tool for monitoring land surface dynamics. There are relatively few systematic reviews of the STF method. Bibliometrics is a valuable method for analyzing the scientific literature, but it has not yet been applied to the comprehensive analysis of the STF method. Therefore, in this paper, we use bibliometrics and scientific mapping to analyze the 2967 citation data from the Web of Science from 1991 to 2023 in a metrological manner, covering the themes of STF, data fusion, multi-temporal analysis, and spatial analysis. The results of the literature analysis reveal that the number of articles displays a slow to rapid increase during the study period, but decreases significantly in 2023. Research institutions in China (1059 papers) and the United States (432 papers) are the top two contributors in the field. The keywords “Sentinel”, “deep learning” (DL), and “LSTM” (Long Short-Term Memory) appeared most frequently in the past three years. In the future, remote sensing spatiotemporal fusion research can address more of the limitations of heterogeneous landscapes and climatic conditions to improve fused images’ accuracy.

Robust and secure ranging is essential for numerous light detection and ranging (LiDAR) applications. Traditional LiDAR systems, however, are susceptible to deception jamming, such as intercept-and-resend spoofing attacks, due to their use of classical signals for interrogating non-cooperative targets. While quantum-secured imaging protocols have been proposed to counter these attacks, practical models have been scarce. This paper presents a quantum-secured LiDAR protocol using time-bin phase-encoded quantum states for simultaneous ranging and security assessment. Ranging is done via cross-correlating signals, and security assessment by statistically analyzing error rates. We develop an analytical model to evaluate the system’s resilience against intercept-resend spoofing attacks, demonstrating through numerical simulations that such attacks can be detected with high probability and low false-alarm rates under certain conditions. The scheme is robust against polarization disturbances and phase drifts, and can be implemented using existing technology, signifying its potential in quantum radar applications to improve the security and reliability of optical ranging and imaging systems.

By extending synthetic aperture technology from a microwave band to laser wavelength, the synthetic aperture ladar (SAL) achieves extremely high spatial resolution independent of the target distance in long-range imaging. Nonlinear phase correction is a critical challenge in SAL imaging. To address the issue of phase noise during the imaging process, we first analyze the theoretical impact of nonlinear phase noise in imaging performance. Subsequently, a reconstruction and compensation method based on orthonormal complete basis functions is proposed to mitigate nonlinear phase noise in SAL imaging. The simulation results validate the accuracy and robustness of the proposed method, while experimental data demonstrate its effectiveness in improving system range resolution and reducing the peak side lobe ratio by 3 dB across various target scenarios. This advancement establishes a solid foundation for the application of SAL technology in ground-based remote sensing and space target observation.