Yifan Xing

Mineral maps can overstate identification when detectable absorptions remain compatible with several minerals. We present a framework that tests candidate labels for a sensor and scene before assigning them pixel by pixel, retaining family evidence where subclasses remain unresolved. We applied it to ZY1-02E AHSI observations of southern Libya, using background-adjusted matched-subspace, wavelet and shape measures for SWIR absorptions and the complete VNIR feature for ferric iron. Thresholds derived from scene backgrounds were evaluated on held-out blocks using numerical mixtures and independent mineral confusers. The broad 2.30 µm response was readily recovered but accepted 36.2% of tested Al-OH mixtures and was withheld. Conditional calcite and Fe/Mg-OH branches had cross-assignment of at most 1.33%. Among accepted Al-OH pixels, 31.2% remained at family level. Release stability varied: Al-OH passed in four of 13 background-sampling designs, whereas the broad 2.30 µm group failed throughout. ASTER and mapped geology were used to contextualise the evidence and identify eight potential follow-up zones covering 34.5 km², with differing persistence under selection and registration changes. The framework links controlled spectral separability to the level of detail retained in mineral maps. Independent observations are still required to confirm mineral identity and geological origin.

Ion-adsorption type rare earth element (IREE) deposits are critical strategic resources formed under strong lithological, geomorphological, and weathering controls. In Houaphanh Province, Laos, widespread granitic intrusions and tropical monsoon weathering provide favorable conditions for IREE mineralization; however, exploration is limited by rugged terrain, dense vegetation cover, and sparse geological data. This study integrates Landsat 9, ASTER multispectral, and digital elevation data to enhance IREE exploration. Band ratio and principal component analysis (PCA) were applied to extract lithological and alteration features, while six topographic parameters describing elevation, slope, relief amplitude, incision depth, surface roughness, and elevation variability were derived from ASTER GDEM data. These datasets were combined using a weighted overlay to delineate favorable geomorphic zones. Six prospectives zones were identified, and field verification at Nongkhang confirmed 19 IREE ore bodies. The results demonstrate that integrating spectral and topographic indicators significantly improves the accuracy for IREE prediction in tropical, densely vegetated regions, offering a transferable framework for similar geological settings worldwide.