The Xizang–Sichuan region is rich in tourism resources, yet its complex geography and lagging transportation infrastructure have resulted in pronounced spatial disparities in tourism development. From a sustainability perspective, such disparities can lead to a ‘rich-get-richer’ cycle: over-tourism and ecological stress in high-accessibility cores, versus underdevelopment and resource idling in low-accessibility peripheries. To systematically examine the spatial structure of tourism in this region, this study uses counties as basic units and integrates the Analytic Hierarchy Process (AHP) with an improved gravity model for tourism network potential accessibility (TNPA) to assess regional tourism development levels and the network-based accessibility among counties. A comprehensive evaluation framework was established across three dimensions: tourism resource endowment, service capacity, and socio-economic support. Travel times between county centers were obtained from the Amap API, and a TNPA index was computed to reflect each county’s potential for tourism interaction with the rest of the region. Results indicate that resource endowment dominates the evaluation, with scenic quality as the critical factor. TNPA exhibits a pronounced core–periphery differentiation, with Chengdu and surrounding areas forming a high-value network core, while most counties in Xizang show extremely low network potential. Equity analysis reveals a significant imbalance in the distribution of network accessibility between Sichuan and Xizang. Under the baseline setting, the population-weighted Gini coefficient, coefficient of variation, and Theil index reach 0.677, 1.724, and 0.884, respectively, indicating that tourism network potential remains highly concentrated in a limited number of counties. The population-weighted mean TNPA of Sichuan is also far higher than that of Xizang, revealing a distinct interregional accessibility gap. The development–TNPA mismatch analysis further identifies counties where tourism development foundations are relatively strong but network integration remains weak. Robustness checks indicate that the high-development–low-TNPA pattern is not simply an artefact of the median-based classification, with the most evident cases mainly concentrated in Aba and Garze in western Sichuan and a few counties in Xizang. The study highlights the asymmetric relationships among resource endowment, network accessibility, and equity, providing a scientific basis for optimizing cross-regional tourism cooperation and transportation corridors in the Xizang–Sichuan region.

Spectral variations in hydrothermal alteration minerals can provide information on hydrothermal zonation and may inform mineral-exploration interpretation. The Mamupu Cu–Au skarn deposit, located in the southern Yulong porphyry copper belt of eastern Tibet, records multistage skarn formation and hydrothermal alteration. Drill core from six boreholes across the main orebody and its surrounding area was investigated using short-wave infrared (SWIR) and Fourier-transform infrared (FTIR) spectroscopy, focusing on two chlorite types, mica-group minerals, and garnet. Ch-1 Pos2250 decreases with increasing distance to the main orebody (R² = 0.67), whereas the Ch-2 spectral parameters show mixed relationships with this distance variable. Mica-group Pos2200 also decreases with increasing distance to the main orebody (R² = 0.61), while Dep2200 and the crystallinity index show no statistically significant linear relationships. In garnet, the Position of the FTIR feature near 875 cm⁻¹ decreases with increasing distance to the skarn body (R² = 0.36), whereas Height shows no statistically significant linear relationship. Overall, band-position parameters show clearer spatial associations with distance than absorption-depth or intensity-related parameters in the datasets examined. These results provide preliminary constraints on spectral variations associated with alteration and mineralization-related geological environments at Mamupu. However, the observed associations have not been tested independently of lithology, alteration, or mineralization, and the garnet relationship is based on the selected sample subset described below. Their predictive value for untested deep or peripheral areas therefore remains to be evaluated.