Investigation reveals a Moon-based platform can improve monitoring of land cover types, suggesting enhanced Earth observation capabilities.
Moon-based Earth observation is one of the important research contents in future lunar missions such as Chang'e−8 and the International Lunar Research Station. Current remote sensing platforms, including Low Earth Orbit (LEO), Geostationary Earth Orbit (GEO), and Sun-Earth Lagrange 1 (L1) satellites, face inherent limitations in providing the comprehensive angular coverage necessary for robust scientific analysis and detailed surface characterization. This study investigates the unique potential of a Moon-based platform to address these limitations by offering unique multi-angle observation capabilities. We simulate the achievable observation geometries from a Moon-based platform across various latitudes and characterize the multi-spectral radiative properties of key land cover types (evergreen broadleaf forest, snow/ice, desert), validating our simulations against existing Earth Polychromatic Imaging Camera data. Our findings demonstrate that the Moon-based platform's unique angular observation capabilities effectively characterize the distinct bidirectional reflectance properties of various land cover types—from the strong angular dependence of low-latitude evergreen broadleaf forest to the quasi-isotropic tendencies of high-latitude snow/ice and mid-to-low latitude deserts—thereby facilitating accurate monitoring and retrieval across diverse geographical concentrations. This research highlights the potential of a Moon-based platform to provide foundational, multi-angle datasets capable of reducing uncertainty in global Earth system products.
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Guo et al. (2025) studied this question.
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