With global warming, supraglacial lakes play an important role in ice sheet stability and climate change. They are not only the main factors affecting mass balance and sea-level rise but also the key units of surface runoff storage and mass loss. To automatically map the spatiotemporal distribution of supraglacial lakes in Greenland, this paper proposes an attention-based U-Net model with Sentinel-1 SAR imagery. The extraction results show that compared with the traditional network, this method obtains a higher validation coefficient, with an F1 score of 0.971, and it is spatiotemporally transferable, able to realize the extraction of supraglacial lakes in complex areas without ignoring small lakes. In addition, we conducted a case study in the Jakobshavn region and found that the supraglacial lake area peaked in advance between spring and summer due to extreme melting events from 2017 to 2021. Meanwhile, the supraglacial lakes near the 79°N Glacier tended to expand inland during the melting season.

Blind image deblurring is a long-standing challenge in remote sensing image restoration tasks. It aims to recover a latent sharp image from a blurry image while the blur kernel is unknown. To solve this problem, many image priors-based algorithms and learning-based algorithms have been proposed. However, most of these methods are based on a single blurry image. Due to the lack of high frequency information, the images restored by these algorithms still have some deficiencies in edge and texture details. In this work, we propose a novel deep learning model named Reference-Based Multi-Level Features Fusion Deblurring Network (Ref-MFFDN), which registers the reference image and the blurry image in the multi-level feature space and transfers the high-quality textures from registered reference features to assist image deblurring. Comparative experiments on the testing set prove that our Ref-MFFDN outperforms many state-of-the-art single image deblurring approaches in both quantitative evaluation and visual results, which indicates the effectiveness of using reference images in remote sensing image deblurring tasks. More ablation experiments demonstrates the robustness of Ref-MFFDN to the input image size, the effectiveness of multi-level features fusion network (MFFN) and the effect of different feature levels in multi-feature extractor (MFE) on algorithm performance.

The Chinese Chang’E-7 (CE-7) mission is planned to land in the lunar south polar region, and then deploy a mini-flying probe to fly into the cold trap to detect the water ice. The selection of a landing site is crucial for ensuring both a safe landing and the successful achievement of its scientific objectives. This study presents a method for landing site selection in the challenging environment of the lunar south pole, utilizing multi-source remote sensing data. First, the likelihood of water ice in all cold traps within 85°S is assessed and prioritized using neutron spectrometer and hyperspectral data, with the most promising cold traps selected for sampling by CE-7’s mini-flying probe. Slope and illumination data are then used to screen feasible landing sites in the south polar region. Feasible landing sites near cold traps are aggregated into larger landing regions. Finally, high-resolution illumination maps, along with optical and radar images, are employed to refine the selection and identify the optimal landing sites. Six potential landing sites around the de Gerlache crater, an unnamed cold trap at (167.10°E, 88.71°S), Faustini crater, and Shackleton crater are proposed. It would be beneficial for CE-7 to prioritize mapping these sites post-launch using its high-resolution optical camera and radar for further detailed landing site investigation and evaluation.

Most of the driving mechanisms used in micro flapping wing vehicles are gear and linkage transmission mechanisms, which convert the unidirectional rotation of the motor into the reciprocating flapping of the driving mechanism. However, gear and linkage transmission mechanisms occupy a larger space and weight with certain energy losses. This article introduces a drive mechanism that is different from gear and linkage mechanisms, namely the string-based mechanism. In this study, the working principle and various parameters in string-based mechanisms are analyzed, and the flapping trajectory and amplitude of the mechanism is simulated. Following that, this article proposes an improved method of the cam mechanism, designs the trajectory of a cam mechanism, and a physical design is carried out with a driving mechanism width of 22 mm. Subsequently, the experiments are conducted to compare the flapping trajectory of the actual mechanism with the simulation trajectory, thereby verifying the simulation accuracy. The results prove that, in a string-based mechanism, the ratio of the radius of the pulley to the installation radius of the double-layer bearings has a direct impact on the flapping amplitude, and optimizing the design of cam mechanisms can effectively reduce the tensile and relaxation phenomena in string-based mechanisms. The above conclusion was verified in physical experiments, where the modified cam mechanism effectively reduced the stuck phenomenon in the string-based mechanism.

In the design of flapping-wing micro-size air vehicles capable of hovering, wings serve as the primary source of hovering power, making the analysis of aerodynamics and aerodynamic efficiency crucial. Traditional quasi-steady models treat the wings as single rigid plane, neglecting the deformable characteristics of flexible wings. This paper proposes a multi-plane method that, in conjunction with various design parameters of flexible wings in a two-dimensional plane, analyzes their deformation characteristics under the assumption of multiple planes in three-dimensional space, and describes the deformation of wings during flapping. By combining the quasi-steady aerodynamic model, aerodynamic analysis of the deformed wings can be conducted. The relationship between the slack angle, wing flapping position, and wing deformation are analyzed, along with their effects on aerodynamics and aerodynamic efficiency. Experiments validate the deformation patterns of wings during flapping and compare the simulated aerodynamic forces with measured ones. The results indicate that wing deformation can be accurately described by adjusting the parameters in the multi-plane method and that the aerodynamic analysis using this method closely approximates the average lift results. Additionally, the multi-plane method establishes a connection between wing morphology and aerodynamic forces and efficiency, providing valuable insights for aerodynamic analysis.