High-resolution digital elevation models (DEMs) of permanently shadowed regions (PSRs) at the lunar South Pole are crucial for upcoming exploration missions. Recent advances, such as high-resolution images acquired from ShadowCam, utilize indirect lighting to image PSRs. This provides data for the Shape from Shading (SFS) technique, which can extract subtle topographic details from single-image to reconstruct high-resolution terrain. However, traditional SFS methods are not suitable for complex secondary scattering scenes in PSRs with multiple secondary light sources. To address this issue, a novel secondary scattering SFS (SS-SFS) method is developed for pixel-wise 3D reconstruction of PSR surfaces, which utilizes indirect illuminated imagery and the corresponding low-resolution DEM to generate DEM with high resolution matches the input image. The proposed method effectively extracts and simplifies multiple incident facets associated with each shadowed facet through clustering, while constructing and optimizing the SS-SFS loss function. Experiments were conducted using ShadowCam images of two areas including both PSRs and temporary shadowed areas, to demonstrate the performance of the proposed method. The SS-SFS DEMs effectively capture intricate topographic details, and comparisons with adjusted Lunar Orbiter Laser Altimeter laser points indicate that the SS-SFS DEMs exhibit high overall accuracy. The high-resolution slope map of PSRs was calculated based on the SS-SFS DEMs, and overcome the limitation that surface slope is relatively underestimated from LOLA DEMs. Additionally, the SS-SFS DEMs were comprehensively compared with the traditional SFS DEMs generated using Narrow Angle Camera imagery in a small temporarily shadowed area, revealing strong consistency and further validating the effectiveness of detailed reconstruction. Overall, the proposed SS-SFS method is essential for generating high-resolution DEMs of PSRs, supporting future lunar South Pole exploration missions.

The black soil region of Northeast China is the largest commercial grain production base in China, accounting for about 25% of the total in China. In this region, the water erosion is prominent, which seriously threatens China's food security. It is of great significance to effectively identify the erosion-prone points for the prevention and control of soil erosion on the slope of the black soil region in Northeast China. This article takes the Tongshuang small watershed (Heilongjiang Province in China) as an example, which is dominated by hilly landforms with mainly black soil and terraces planted with corn and soybeans. Based on the 2.5 cm resolution Digital Elevation Model (DEM) reconstructed by unmanned aerial vehicles (UAVs), we explore the optimal resolution for hydrological simulation research on sloping farmland in the black soil region of Northeast China and explore the critical water depth at which erosion damage occurs in ridges on this basis. The results show that the following: (1) Compared with the 2 m resolution DEM, the interpretation accuracy of field roads, wasteland, damaged points, ridges and cultivated land at the 0.2 m resolution is increased by 4.55-27.94%, which is the best resolution in the study region. (2) When the water depth is between 0.335 and 0.359 m, there is a potential erosion risk of ridges. When the average water depth per unit length is between 0.0040 and 0.0045, the ridge is in the critical range for its breaking, and when the average water depth per unit length is less than the critical range, ridge erosion damage occurs. (3) When local erosion damage occurs, the connectivity will change abruptly, and the remarkable change in the index of connectivity (IC) can provide a reference for predicting erosion damage.

This study focused on applying numerical simulations to assess damaged areas caused by debris flows, employing the LS-RAPID program while emphasizing the importance of terrain information. Terrain information used in the numerical simulation included a 1:5000 digital terrain map and a digital surface model using an unmanned aerial vehicle. Quantification of the amount of soil that collapsed from the road embankment slope, which is the source of the debris flow, facilitated the computation of the debris flow that closely resembled real-world conditions. In particular, incorporating the high-resolution digital surface model (DSM) with 3-cm topographic information resulted in an interpretation of the actual soil flow damage range that is similar to actual observations of the digital elevation model (DEM), which had 1-m grid topographic information. This difference arises from DSM as it reflects the information of low hills downstream. The range of damage changed as the direction of the debris flow changed because of the low hill. Many variables need adjustment for the accuracy of debris flow numerical simulation. However, the direction and range of flow vary greatly depending on topographic information, highlighting the necessity of applying high-resolution terrain information. The results of debris flow simulations with high-resolution terrain information are expected to improve accuracy and help prepare risk or damage maps.