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 Pulang porphyry copper deposit (PCD), one of the main potential areas for copper resource exploration in China, exhibits typical porphyry alteration zoning. However, further investigation of the indicative significance of alteration minerals, additional insight into metallogenic characteristics, and prospecting guidelines continue to be challenging. In this study, ASTER and WorldView-3 data were used to map hydrothermal alteration minerals by employing band ratios, principal component analysis, and spectrum-area techniques; and subsequently, the indication significance of alteration minerals was studied in-depth. The following new insights into the metallogenic structure and spatial distribution of alteration zoning in Pulang PCD were obtained and verified. (1) A new NE trending normal fault, passing through the northeast of Pulang PCD, was discovered. (2) Two mineralization alteration centers, exhibiting alteration zoning characteristics of potassic-silicified, phyllic, and propylitic zones from the inside to the outside, were observed on both sides of the fault. (3) At the junction of the redivided potassic-silicification and phyllic zones, favorable prospecting potential areas were delineated. This study shows that the spectral/multi-sensor satellite data are valuable and cost-effective tools for the preliminary stages of porphyry copper exploration in inaccessible and remote areas around the world.

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.

Gold is a vital strategic resource for many countries. The Laozhaiwan area is an important gold resource base in Yunnan Province and even nationwide. Conducting mineral resource exploration in this region to increase gold reserves is of great significance. The application of remote sensing technology in mineral resource exploration is a green and efficient technical approach, which has been widely utilized in the field of mineral resource prospecting. This study selects the Laozhaiwan area in the southeastern part of Yunnan Province as the research region. Linear and ring structures were extracted using the remote sensing visual interpretation method based on Sentinel-2A multispectral data. Additionally, Sentinel-2A, ASTER, and ZY1-02D data were used to extract iron-stained, hydroxyl, silicification, and limonite alteration information through Principal Component Analysis (PCA) and Spectral Angle Mapper (SAM) methods. Additionally, 50 linear structures and 12 ring structures were extracted. A comprehensive analysis of geological data reveals that alteration minerals and linear-ring structures are closely related to mineralization, providing valuable indicators for mineral resource exploration. By comprehensively analyzing the alteration information and remote sensing interpretation results of the linear-ring structures, two prospective areas for mineral exploration were delineated. Field investigations and petrographic studies confirmed the reliability of remote sensing technology in mineral exploration. The mineral exploration method based on multi-source remote sensing technology can clearly reflect various alteration information and linear-ring structural data. It provides remote sensing geological insights for geological survey work and has great application potential in the field of mineral resource exploration.

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.