Conference Agenda

LunarDEM2025 is a lunar topography model (±60°) created by fusing JAXA’s SLDEM2013, CAS’s CE2TMap2015 and NASA’s LOLA laser altimetry tracks. A tile-based, terrain-aware co-registration aligns photogrammetric DEMs to LOLA points, while a slope-constrained residual-compensation filter eliminates striping, voids and artefacts. The resulting dataset shows visibly smoother relief, smaller vertical biases and fewer tile-boundary discontinuities than its predecessor SLDEM2015. The product is ready for landing-site analysis, rover path planning and various other applications.

After completing the 1:2,500,000-scale (1:2.5 M) lunar geologic atlas, our team began exploring the techniques and work flows for compiling larger scale lunar geological maps. Geologic maps integrate multidimensional information such as lithology, structure, and geologic age. Using the Copernicus crater region (0°–16°N, 30°W–10°W) as a case study, this research develops a 1:1,000,000-scale (1:1 M) regional geologic map and, in turn, explores the lithologic and structural classification systems applicable to lunar geologic maps at different scales. Based on imagery, topography, spectral, gravity, and sample data, we analyze geologic features including impact craters, impact basins, compositions, and structures, and subsequently delineate geological units. In the study area, the Copernicus crater and Imbrium basin represent the most prominent geological events and can serve as benchmarks for relative age determination. The cross-cutting relationships among geological units, together with existing absolute age constraints (from isotopic dating and crater size-frequency distribution chronology), are used to establish the stratigraphic relationships among mapped features and layers, ultimately producing a regional geologic map. Based on this map, the geological evolution history of the region is reconstructed.

High-accuracy planetary mapping products are increasingly required for landing-site assessment, precision navigation, and future surface operations on the Moon and Mars. Although massive orbital remote sensing images are available, the geometric accuracy and spatial resolution of many existing mapping products is still insufficient for engineering applications. A major bottleneck is large-scale bundle adjustment, whose reliability is strongly affected by data quality, control network strength, as well as engineering experience. Compared with Earth observation photogrammetry, planetary mapping faces great challenges such as heterogeneous sensor models, complex illumination, sparse absolute control. This paper summarizes a practical quality control framework for large-scale bundle adjustment of planetary remote sensing images. The workflow is divided into four coupled stages: data preprocessing, control network construction, parameter setting, and accuracy evaluation. The framework is distilled from previous planetary mapping studies, open-source software platforms and our practical experience in processing tens of thousands of planetary images. Experiments using LRO NAC datasets demonstrate that satisfactory bundle adjustment results can be achieved when the proposed strategy is applied. The framework improves the overall efficiency, controllability, and reliability of large-scale planetary photogrammetric processing.

China has successfully carried out the Chang'e-1 to Chang'e-6 lunar missions and the Tianwen-1 Mars mission. In these missions, planetary photogrammetry and remote sensing technologies provide timely spatio-temporal information services across all phases of the missions, playing a crucial supporting role in ensuring the mission safety and scientific output. In the current era of artificial intelligence (AI), the deep integration of photogrammetry and remote sensing, geomatics, and artificial intelligence is gradually evolving into Spatio-Temporal Intelligence (STI). This paper presents an overview of the advances and applications of STI in China’s lunar and Mars explorations, and discuss the future directions of STI in deep space exploration.

Based on microwave radiometer (MRM) data from China's Chang'e (CE)-1/2 satellites, the Brightness Temperature Difference (TBD) technique offers a method for probing lunar regolith properties. However, its global application is compromised by systematic latitudinal biases and an unverified link to subsurface deposits.

This study introduces a novel parameter, the effective TBD (TBDeff), to overcome these limitations. The methodology first defines an equivalent TBD (eTBD), simulating the TBD for a location as if it were on the lunar equator to mitigate latitudinal effects. Recognizing inherent limitations in this simulation, a supplementary parameter (sup_TBD) is derived. TBDeff is then developed by integrating sup_TBD with the observed TBD (TBDobs) from CE-2 data.

Results demonstrate that TBDeff successfully removes latitudinal bias on a global scale, enabling clearer discrimination between lunar maria and highlands. Furthermore, extensive low-TBDeff signals in polar regions (>85°) suggest a new potential for detecting subsurface deposits in permanently shadowed areas.

Crucially, correlation analysis with (FeO+TiO₂) abundance reveals that TBDeff exhibits a significantly stronger relationship with regolith composition than traditional TBD or simple brightness temperatures (TB), especially at lower frequencies (reaching a correlation coefficient of 0.86 at 3.0 GHz). This confirms that (FeO+TiO₂) abundance is a key factor influencing the dielectric properties of subsurface materials, a effect previously obscured by latitudinal interference. The TBDeff method thus provides a more reliable tool for interpreting lunar composition from microwave data.

This study analyzed and compared in situ spectral obtained by the Chang’E-3(CE-3) and Chang’E-4(CE-4) rovers, laboratory spectra of Chang’E-5(CE-5) soils and remote sensing spectra. The remote sensing spectra exhibit significantly darker and shallower absorption features than laboratory or in situ spectra, reflecting highly weathered nature of the undisturbed lunar surface. The spectral upturn even just right >2 μm can be contributed by thermal emission, revealing micro-scale temperature variations and low thermal inertia of lunar soils. CE-5 sample spectra show significantly higher reflectance and absorption depths than in situ and remote sensing, indicating samples are fresh and couldn’t represent pristine/true lunar surface. The CE-5 samples provide a new ground truth for estimating the TiO2 content of young basalts, which have the largest uncertainty in TiO2 content. Contrary to traditional opinion, CE-3 in situ spectra revealed that the effect on the spectral slope caused by space weathering is wavelength-dependent: the visible slope (VS) decreases not increases. The optical effects of space weathering and TiO2 are identical: both reduce albedo and blue the spectra. This suggests that a new TiO2 abundance algorithm is needed.