Hydrothermal alteration minerals are an effective prospecting indicator. Advanced spaceborne thermal emission and reflection radiometer (ASTER) satellite data are some of the most commonly adopted multispectral data for the mapping of hydrothermal alteration minerals. Compared to multispectral data, hyperspectral data have stronger ground object recognition ability. Chinese Gaofen-5 (GF-5) is the first hyperspectral satellite independently developed by China that has the advantages of both wide-width and high-spectral-resolution technology. However, the mapping ability of GF5 data for hydrothermal alteration minerals requires further study. In this study, ASTER and GF-5 satellite data were implemented to map hydrothermal alteration minerals in the Longtoushan Pb-Zn deposit, SW China. Selective principal component analysis (SPCA) technology was employed to map iron oxide/hydroxides, argillic, quartz, and carbonate minerals at the pixel level using ASTER data, and the mixture tuned matched filtering (MTMF) method was implemented for the extracted hematite, kaolinite, calcite, and dolomite at the sub-pixel level using GF-5 data. When mapping the hydrothermal alteration minerals, the distribution features of the hydrothermal alteration minerals from the Longtoushan Pb-Zn deposit were systematically revealed. A comprehensive field investigation and petrographic study were conducted to verify the extraction accuracy of the hydrothermal alteration minerals. The results showed that the overall accuracies for the ASTER and GF-5 data were 82.6 and 92.9 and that the kappa coefficients were 0.78 and 0.90, respectively. This indicates that the GF-5 data are able to map hydrothermal alteration minerals well and that they can be promoted as a hyperspectral data source for mapping systematic hydrothermal alteration minerals in the future.

The North Konawe region in Indonesia, known for its lateritic nickel (Ni) deposits, holds significant potential for obtaining Ni resources. However, the complex topographic conditions of this area pose challenges. Exploring the application of remote sensing technology to reveal the spectral response mechanism of Ni grade from high-precision multispectral data and inversion of Ni grade represents a novel direction in future Ni resource exploration. Traditional remote sensing inversion methods solely consider the spectral characteristics of sample data and ignore vital geospatial location information. As a result, efficiently obtaining regional details of target substance content over large areas has become challenging. The introduction of the geographically weighted regression (GWR) method offers an opportunity for fine-grained Ni grade inversion based on remote sensing. This study focused on the E and K blocks within the lateritic Ni mining area in North Konawe. Through utilizing the WordView-3 multispectral data which exhibits immense potential in quantitative remote sensing inversion studies, GWR was employed to integrate spectral features and spatial information. The goal was to reveal the correlation between multispectral remote sensing data and Ni grade. The obtained results were then compared and analyzed with multiple linear regression (MLR) and back propagation neural network (BPNN) models. The findings revealed that GWR achieved the highest coefficient of determination R² of 0.96, surpassing MLR and BPNN values of 0.05 and 0.17, respectively. Additionally, GWR exhibited the lowest root mean square error of 0.04, which was lower than those of MLR and BPNN with the values of 0.25 and 0.23, respectively. These results confirmed the enhanced stability and accuracy of the GWR method compared to MLR and BPNN. Furthermore, GWR effectively mapped the spatial distribution trends of Ni grades in the study area, providing evidence of the method’s effectiveness in Ni grade inversion. The study also delved into the inversion effect of the GWR method in areas with varying weathering crust thickness and vegetation cover. The research revealed that higher values of weathering crust thickness negatively impacted the inversion effect. However, the influence mechanism of vegetation cover on Ni grade inversion necessitated further investigation. These results served as a significant demonstration of the remote sensing inversion of mineral resource grades in similar areas. They provided valuable insights for future exploration and decision-making processes.

On 2 January 2022, an earthquake of M_s 5.5 occurred in Ninglang County, Lijiang City, the earthquake-prone area of northwestern Yunnan. Whether this earthquake caused significant deformation and thermal anomalies and whether there is a relationship between them needs further investigation. Currently, multi-source remote sensing technology has become a powerful tool for long-time-series monitoring of earthquakes and active ruptures which mainly focuses on single crustal deformation and thermal anomaly. This study aims to reveal the crustal deformation and thermal anomaly characteristics of the Ninglang earthquake by using both Interferometric Synthetic Aperture Radar (InSAR) and Robust Satellite Techniques (RST). First, Sentinel-1A satellite SAR data were selected to obtain the coseismic deformation field based on Differential InSAR (D-InSAR), and the Small Baseline Set InSAR (SBAS-InSAR) technique was exploited to invert the pre- and post-earthquake displacement sequences. Then, RST was used to extract the thermal anomalies before and after the earthquake by using Moderate Resolution Imaging Spectroradiometer Land Surface Temperature (MODIS LST). The results indicate that the seismic crustal deformation is dominated by subsidence, with 23 thermal anomalies before and after the earthquake. It is speculated that the Yongning Fault in the deformation area is the main seismogenic fault of the Ninglang earthquake, which is dominated by positive fault dip-slip motion. Meanwhile, the seismic fault system composed of NE- and NW-oriented faults is an important factor in the formation of thermal anomalies, which are accompanied by changes in stress at different stages before and after the earthquake. Moreover, the crustal deformation and seismic thermal anomalies are correlated in time and space, and the active rupture activities in the region produce deformation accompanied by changes in thermal radiation. This study provides clues from remote sensing observations for analyzing the Ninglang earthquake and provides a reference for the joint application of InSAR and RST for earthquake monitoring.

The Kungurian Stage in the early Permian was a transitional glacial age between the late Paleozoic icehouse and the early Mesozoic super-greenhouse period This stage offers an excellent opportunity to study the co-evolution between global carbon cycles and environments. This study presents facies and carbon isotope variations in a new carbonate section in the Lower Yangtze region of South China in order to understand the linkage between carbon cycle fluctuation, sedimentary environment, and climate change. Based on the sedimentary facies analyses of the Chihsia Formation (Kungurian), seven facies types were identified and grouped into lower slope, upper slope, and platform facies associations. The facies analyses show that the Kungurian Stage experiences two transgressive-regressive cycles; paleoclimatic changes controlled the sedimentary records and sea level fluctuations. Early Kungurian carbonate rocks record the presence of the short-lived Kungurian carbon isotopic event (KCIE). The rapid negative carbon isotope of the KCIE was closely related to the huge CO₂ emission. A warming climate could have slowed down oceanic ventilation rates and accelerated stratification of seawater. The resulting anoxic environment led to a sharp decline in biological species. In the middle Kungurian, the intensity of volcanic activity gradually weakened and the climate turned cold, which accelerated oceanic ventilation rates and led to increased oxygenation of deep-shelf water masses. The higher Δ¹³C values supported enhanced primary productivity and photosynthesis, which promote the prosperity of biological species. This study provides a new perspective for better understanding the links between marine carbon cycle fluctuations, climate change, and environments during the icehouse to greenhouse conversion period.

Large-scale phosphogenesis occurred globally during the early Cambrian Epoch, meanwhile large phosphorite deposits, represented by the Zhijin deposit in Guizhou and Kunyang deposit in Yunnan, were formed in South China. In order to explore similarities and differences of mineralization mechanisms and constraining factors of the Zhijin and Kunyang deposits, mineralogical and geochemical analyses of P-bearing rock series in the Xinhua oreblock of the Zhijin deposit and the Wangjiawan oreblock of the Kunyang deposit have been carried out in this paper. The results show that grain sizes of both collophane and apatite minerals in the P-bearing rock series of the Kunyang deposit are significantly larger than those of the Zhijin deposit, implying that the P-bearing rock series in the Kunyang area were formed in a relatively shallow seawater with strong hydrodynamic condition; There are significantly-weakly positive relationships between P₂O₅ and Al₂O₃, SiO₂, Zr/Hf and Sr contents in P-bearing rock series of both Zhijin and Kunyang deposits, indicating that terrestrial weathering input provided the material sources of phosphorous in Cambrian Ocean; The variation ranges of redox-sensitive elements (V, Ni, Cr, Mo, U) contents and Ce/Ce* values of P-bearing rock series in the Zhijin area are larger than those of P-bearing rock series in the Kunyang area, showing that there was a relative strongly fluctuated oxic–suboxic deposition condition in the zhijin area comparing to the Kunyang area; The P-bearing rock series of the Zhijin and Kunyang deposits have ″hat-shaped″ PAAS-normalized REE distribution patterns, with characteristics of negative Ce anomalies, significantly positive Y anomalies, and negative or weak-positive Eu anomalies Eu anomalies, indicating that their phosphogenetic processes were controlled by biological/organic matters and/or Fe-Mn (oxyhydr) oxides. It is concluded that the formation mechanisms of P-bearing rock series in the Zhijin and Kunyang deposits are highly similar, but differences of lithofacies paleogeographical locations and redox conditions were important reasons for the differences between P-bearing rock series of the Zhijin deposit and those of the Kunyang deposit.

Rapid urbanization and complex topography complicate Urban Heat Island (UHI) spatio-temporal dynamics. Traditional models and coarse-resolution imagery often fail to capture fine-scale, spatially non-stationary seasonal driving mechanisms. This study investigates the multi-dimensional drivers of surface thermal dynamics in Kunming, a typical low-latitude plateau city, using seasonal median LST composite (2018–2025). Integrating eXtreme Gradient Boosting (XGBoost) with eXplainable Artificial Intelligence (XAI) models decoupled the nonlinear impacts of these drivers. Results reveal a seasonal thermal dichotomy: Summer exhibits the most intense UHI effect with extreme peak temperatures, while Spring presents an anomaly where natural and vegetated Local Climate Zones (LCZs) show pronounced warming. SHapley Additive exPlanations (SHAP) analysis identified a seasonal rotation: anthropogenic and structural factors dominate Summer and Autumn warming, whereas natural and topographic regulators govern Spring and Winter. GeoShapley deconstruction demonstrated strong spatial non-stationarity. Building-density warming is amplified in poorly ventilated urban cores, and fragmented vegetation’s cooling is offset by anthropogenic heat during peak summer. This study provides new insights into the seasonal drivers of urban thermal environments in plateau cities.