Airborne hyperspectral remote sensing data provide rapid, non-destructive, and near laboratory quality reflectance spectra for mineral mapping and lithological discrimination, thereby ushering an innovative era of remote sensing. In this study, NEO HySpex cameras, which comprise 504 spectral channels in the spectral ranges of 0.4–1.0 μm and 1.0–2.5 μm, were mounted on a delta wing XT-912 aircraft. The designed flexibility and modular nature of the HySpex aircraft hyperspectral imaging system made it relatively easy to test, transport, install, and remove the system multiple times before the acquisition flights. According to the design fight plan, including the route distance, length, height, and flight speed, we acquired high spectral and spatial resolutions airborne hyperspectral images of Yudai porphyry Cu (Au, Mo) mineralization in Kalatag District, Eastern Tianshan terrane, Northwest China. By comparing the features of the HySpex hyperspectral data and standard spectra data from the United States Geological Survey database, endmember pixels of spectral signatures for most alteration mineral assemblages (goethite, hematite, jarosite, kaolinite, calcite, epidote, and chlorite) were extracted. After a HySpex data processing workflow, the distribution of alteration mineral assemblages (iron oxide/hydroxide, clay, and propylitic alterations) was mapped using the random forest (RF) algorithm. The experiments demonstrated that the workflow for processing data and RF algorithm is feasible and active, and show a good performance in classification accuracy. The overall classification accuracy and Kappa classification of alteration mineral identification were 73.08 and 65.73%, respectively. The main alteration mineral assemblages were primarily distributed around pits and grooves, consistent with field-measured data. Our results confirm that HySpex airborne hyperspectral data have potential application in basic geology survey and mineral exploration, which provide a viable alternative for mineral mapping and identifying lithological units at a high spatial resolution for large areas and inaccessible terrains.

Several techniques, such as chemical methods and inductively coupled plasma mass spectrometry (ICP-MS), are available to accurately determine element content. However, they are time-consuming, labor-intensive, or expensive. Portable X-ray fluorescence spectrometry (pXRF) can be applied in various scenarios, with significantly higher efficiency and cost-effectiveness than laboratory methods. However, it also has limitations such as lower detection capability, relatively high detection limits, and lower accuracy than laboratory methods. In this study, we focused on applying pXRF to determine the elemental content of sediment samples and investigate its use in mineral exploration. A variety of factors influencing the results of pXRF analysis were analyzed. Our results showed that pXRF could detect more than 30 elements in stream sediments. The reliability of pXRF’s measurements was affected by factors such as the kind of element, sediment particle size, sample grinding treatment, count time, averaged element content, standard deviation of content, and range of content variation. The combination of pXRF analysis and laboratory analysis of partial samples is adequate for establishing a multi-element content inference equation. With this equation, it is possible to effectively infer the content gradient of elements, which will provide valuable support for mineral resource exploration.

Natural vegetation on both sides of the Tarim River Basin (TRB) is the only barrier—a critical ecological niche—between the economic belt in the artificial oasis and the Taklimakan Desert. To understand the impact of human activities on the TRB, we explored the spatial and temporal variations in land use/land cover change (LUCC) and landscape pattern evolution from 2000 to 2020. These variations were simulated for 2030 with the 20 years of data using the cellular automata–Markov model and geographical information system analyses. The results predicted substantial LUCCs in the lower reaches of the Tarim River (TRlr), with 3400 km² (20.29%) of the total area (16,760.94 km²) undergoing changes. Wetland, artificial land, grassland, farmland, and forestland areas increased by 578.59, 43.90, 339.90, 201.62, and 536.11 km², respectively, during the period from 2020 to 2030. The only decreases were in the Gobi/other deserts and bare soils (1700.13 km²). We also determined current and future changes in TRlr landscape pattern indices at the class and landscape levels. Combined with a field survey and hydrological data, theoretical support for effective land use management strategies is provided. The findings offer a scientific basis for future ecological civilization construction and sustainable development in the TRB.

Rock geochemical methods are effective for geological surveys, but typical sampling and laboratory-based analytical methods are time-consuming and costly. However, using visible–near-infrared spectroscopy to estimate the metal element content of rock is an alternative method. This study discussed the potential of hyperspectral estimation of Cu and its significant associated elemental content. Ninety-five rock samples were collected from the Kalatage Yudai copper–nickel deposit in Hami, Xinjiang. The effects of different spectral resolutions, spectral preprocessing, band indices, and characteristic band selection on the estimation of the element contents of Fe, Cu, Co, and Ti were investigated. The results show that when the spectral resolution is 5 nm, good results are obtained for all four metal elements, Fe, Cu, Co, and Ti, with the coefficients of determination R² reaching 0.54, 0.59, 0.41, and 0.78, respectively. The best results are obtained for all transformed spectra with continuum removal, inverse transformation, continuum removal, and logarithmic transformation, respectively. In addition, the accuracy of the estimation models constructed by combining band indices and feature band selection was superior compared with full-band spectra for Fe (R² = 0.654, MAE = 1.27%, and RPD = 1.498), Cu (R² = 0.694, MAE = 20.509, and RPD = 1.711), Co (R² = 0.805, MAE = 2.573, and RPD = 2.199), and Ti (R² = 0.501, MAE = 0.04%, and RPD = 1.412). The results indicate that using band indices can provide a more accurate estimation of metal element content, providing a new technical method for the efficient acquisition of regional mineralization indicator element content distribution.

The West Kunlun represents one of the largest and most economically significant rare metal metallogenic belts in NW China. The newly discovered Dahongliutandong Li deposit is the first Li deposit identified within the Permian Huangyangling Group in this region, and its discovery has important implications for regional lithium exploration. In this study, whole-rock major and trace-element geochemistry and cassiterite U–Pb isotope data from both Li-poor and Li-rich pegmatites of the Dahongliutandong deposit were analyzed to constrain the mineralization age and tectonic setting. Geochemically, the pegmatites are characterized by high SiO₂ (70.57–78.50 wt%), low TiO₂, MnO, and MgO (<0.2 wt%), and strongly peraluminous signatures (A/CNK = 1.45–1.95). They exhibit coherent chondrite-normalized REE patterns with LREE enrichment and negative Eu anomalies (Eu/Eu* = 0.03–0.77), along with consistent enrichment in LILEs (e.g., Rb, U, K) and depletion in HFSEs (e.g., Nb, Ti) on primitive mantle-normalized spider diagrams, suggesting a common magmatic source or evolutionary path. Cassiterite U–Pb dating yielded consistent lower-intercept ages of 208 ± 11 Ma (MSWD = 0.86) for Li-poor pegmatites and 206 ± 5 Ma (MSWD = 1.7) for Li-rich pegmatites, both indicating Late Triassic mineralization. Combined with regional geology, these data suggest that Li mineralization was likely related to post-collisional extension following the closure of the Paleo-Tethys Ocean. This study provides new insights into regional rare metal mineralization in the West Kunlun orogenic belt.